Most of us know the story of Silicon Valley.

In 1939, Bill Hewlett and Dave Packard started their electronics company in a garage in Palo Alto. That little operation helped give rise to one of the greatest concentrations of technological innovation the world has ever seen.

But there’s another localized American technology story that never attracted as much attention.

It’s been taking place about 3,000 miles east, in the suburbs of Washington, D.C.

Back in the 1990s, an early internet exchange called Metropolitan Area Exchange-East, or MAE-East, helped turn Northern Virginia into one of the busiest crossroads of the young internet. Internet companies such as UUNET and America Online established major operations in the area, drawn by its communications infrastructure, proximity to the federal government, and growing concentration of technology businesses.

As more companies arrived, the region became an increasingly attractive place for still more companies to build. Internet connections were plentiful, skilled workers were nearby, and local officials welcomed the development.

Over the following decades, the area became known as Data Center Alley — one of the world’s largest concentrations of data centers.

But today, Data Center Alley is looking more like cul-de-sac. Growth is coming to a halt.

Just west of Data Center Alley’s heart in Loudoun and Prince William counties sits Fauquier County. With AI’s enormous appetite for computing power, Fauquier seemed a natural place for the next wave of development.

Developers introduced nine business-park data center proposals to Fauquier. But only one gained approval. The other eight did not.

Then, on October 8, the Fauquier County Board of Supervisors voted to adopt new zoning rules that make data center construction even more restrictive.

Not exactly the welcome mat developers were hoping to find.

And the obstacles don’t end with local opposition. Developers are also discovering that securing enough electricity can be just as difficult as securing permission to build.

Now, Fauquier hasn’t stopped the AI buildout completely. But its new zoning provide a glimpse of the future. Would-be data center builders face a growing list of obstacles and expenses: New projects will take longer, face continuous permitting roadblocks, and incur rising costs. And in an industry committing hundreds of billions of dollars to infrastructure and running on borrowed money, time is expensive.

In today’s Smart Money, I’ll walk you through what’s happening in this Virginia county, why it matters beyond the county itself, and how to position your portfolio for the next phase of the AI trade.

When Building Becomes the Hard Part

The obstacles facing developers in Fauquier fall into three categories. And each one creates a financial problem for the companies trying to build the infrastructure behind AI.

First, localities are cancelling projects before they ever get off the ground. One of the eight withdrawn business-park proposals in Fauquier featured a 2.2-million-square-foot campus near Remington. Another developer abandoned its data center plans and will build homes instead.

Second, projects face mounting delays. Amazon.com Inc. (AMZN) won approval for a $550 million data center in Warrenton in February 2023. Residents sued to block the project, and more than three years later, it remains tied up in court.

Third, projects are incurring rising costs. Remington Technology Park, approved back in 2018, still can’t get enough electricity from the local grid. In July, county supervisors approved a plan for hundreds of natural gas fuel cells and backup diesel generators. Without that workaround, the development could face delays until at least 2030.

Think about that. In the region that helped build the modern internet, developers are struggling to secure the land, legal approvals, and electricity needed to build its next generation of infrastructure.

Delays Cost Money, and Debt Doesn’t Wait

In my recent work, I’ve described how a two-sided vise squeezes the life out of every major tech boom…eventually .

One side is the Revenue Jaw: technological advances that make services cheaper to provide, pushing down what companies can charge.

The other side of the vise is the Expense Jaw: the rising cost of building and operating the infrastructure behind the boom.

And we’ve just seen three examples of that Expense Jaw tightening in Fauquier County.

Every year spent in court can mean another year before a project starts generating revenue. Every permitting hurdle also adds time and expense. Every dollar spent generating electricity on-site adds to the cost of construction. And every project that developers must redesign, or abandon completely, impairs the prospective return on investment.

Now, Fauquier isn’t an outlier. More than 300 towns, cities, and counties across America have adopted data center moratoriums or bans, according to research firm SemiAnalysis. And according to Gallup, 7 in 10 Americans oppose building a data center in their area.

A big reason is electricity bills. People understandably worry they’ll pay more for power to support a boom whose benefits they may never see.

Residents aren’t the only ones facing higher bills. The tech giants first funded the AI buildout from their considerable cash reserves. Increasingly, they’re borrowing to keep it going, and every delay makes that debt more expensive to carry.

And debt doesn’t wait. As the late Charlie Munger, longtime associate of Warren Buffett, bluntly said: “The liabilities are always 100% good; it’s the assets you have to worry about.” Debt shows up every day, rain or shine, and demands its payment on schedule.

In other words, the money you owe is real and unavoidable. The money you hope to earn from your investment is another matter entirely.

That’s an uncomfortable distinction when you’re spending billions on infrastructure that might not begin generating revenue for years.

To be fair, the buildout continues. Remington Technology Park got its power plan approved. The hyperscalers keep raising their spending budgets. And as AI becomes more efficient, demand for computing power will likely increase.

The demand for AI isn’t imaginary. Neither are the obstacles to supplying it.

But the Expense Jaw alone doesn’t end a boom…

Positioning Before the Vise Closes

There’s more danger ahead if the Revenue Jaw closes, too, As AI becomes cheaper to provide, competition could push down what companies can charge, even as construction costs keep climbing and debt payments come due.

Again, the AI buildout isn’t stopping. But it’s encountering delays and growing more expensive in places like Fauquier County. And those costs can fall hardest on the companies financing the infrastructure at the center of the boom: the “AI Builders.”

History suggests that even excellent companies can become disappointing investments when they spend too much building infrastructure that eventually becomes cheaper and more plentiful.

The internet was a tremendous success. That didn’t prevent investors in some of its most important infrastructure companies from losing fortunes.

The companies that come out ahead are often the “Appliers,” businesses that put the new technology to work once it becomes cheap and abundant. They don’t need to own the infrastructure. They just need to find profitable ways to use it.

That’s why I urge you to watch my recent presentation.

In it, I explain all this in more detail, reveal which companies sit within AI’s “vise,” and where I believe investors should look instead. I also name the No. 1 AI Applier to buy right now.

Click here to check it out.

When the first internet companies arrived in Northern Virginia, few could have predicted that the region would become the world’s data center capital.

I believe the AI Revolution will prove every bit as consequential. But as the developers in Fauquier County are discovering, building the next technological empire can be a lot more expensive and complicated than anyone anticipated.

The technology may succeed spectacularly. That doesn’t guarantee that everyone financing its infrastructure will.

That’s why I’m paying close attention to who’s footing the bill… and who’s positioned to enjoy the benefits.

Regards,

Eric Fry

The post As the AI Buildout Slows Down, Here’s What to Do Next appeared first on InvestorPlace.

In 1893, America’s railroad boom came to a screeching halt. 

The industry had spent two decades borrowing vast fortunes to lay thousands of miles of track, which the country now had too much of. When the money ran out, the Union Pacific, the Northern Pacific, and the Santa Fe railroads went into receivership. Railroad stocks lost more than 60% of their value, and it would take the industry years to dig out. 

That same September, a former railroad station agent from Minnesota renamed his struggling mail-order business. 

He called it Sears, Roebuck and Co. 

Now, Richard Sears never built a railroad. He didn’t have to. Instead, he used the overbuilt network left behind to ship watches… sewing machines… and eventually entire houses to families across the country. In 1906, Sears became the first major retail IPO in American history, and sales rose 125-fold to $50 million by the following year. 

The men who built the railroads went broke. The man who applied them became a household name. 

I bring this up because InvestorPlace Senior Analyst Eric Fry believes the AI boom is starting to split the same way. 

On one side are the AI Builders. These are the chipmakers, data center firms, and frontier AI labs borrowing hundreds of billions of dollars to lay the “track” of the AI Revolution. Many of these stocks are priced to perfection. 

On the other side are the AI Appliers: companies that never touch a “shovel.” These are companies like Sears that are using what others have built or are supplying them with products they can’t make for themselves. 

Eric calls the coming split the AI Separation, and he expects it to accelerate on November 4, the morning after the midterms. 

He explains exactly how it unfolds, and names his No. 1 AI Applier for free, in his new presentation. You can watch it here. 

In the meantime, I’d like to discuss three AI Appliers that I’m recommending: companies that profit from the AI buildout without paying for it, at prices that still leave room for upside. 

AI Applier Stock to Buy No. 1: Applying AI to Travel 

In 2000, Eric recommended shares of Humana Inc. (HUM), a health insurance firm. Many experts were fearful that the internet would bypass the need for health insurers, and investors took the company’s declining earnings as evidence to get out. 

But Eric’s healthcare pick would end up returning more than 10X. Rather than get replaced by the internet, Humana used the technology to lower costs, improve throughput, and mint small fortunes for its remaining investors. 

A similar fear is now rippling through the software industry. People are becoming concerned that AI chatbots could replace vast swaths of the digital economy, and my first pick is a sold-off online travel agent that’s using AI, rather than getting replaced by it: 

Booking Holdings Inc. (BKNG). 

The owner of Booking.com, Agoda, Priceline, KAYAK, and OpenTable is the largest travel company in the world. It is also one of the most capital-efficient companies in existence, requiring just $0.35 billion of capital expenditure to maintain almost $30 billion of revenue. 

The firm has faced growing fears that chatbots could replace Booking.com. After all, roughly a quarter of Americans now use AI to help plan trips. BKNG shares are down 25% since September. 

But Booking.com is quite difficult for AI to replace.  

• Inventory: 90% of its hotel bookings come from independent hotels (which no AI agent can contact individually). 
• Payments: The company supports payments in 50+ currencies and has existing payment portals with its hotel clients. 
• Quality Assurance: Booking through a dedicated site reduces the chance of something going wrong (i.e., a chatbot hallucinating and buying the wrong ticket). 

That’s why both Google and OpenAI use Booking.com to help power their own agentic booking systems. BKNG already has the necessary systems in place.  

In addition, Booking is using AI to keep growing its business. It is combining AI models with its own proprietary information to convert more searches into reservations, upsell more in each trip, and reduce the cost of serving customers. Analysts expect earnings per share to rise 15% this year and then accelerate to 18% in 2027 as these efforts pay off. 

And so, the recent selloff creates an opportunity to buy shares of this blue-chip AI Applier. Shares are likely worth at least $200, and up to $220 in a bull case. 

AI Applier Stock to Buy No. 2: A Riskier Retailer 

Petco Health and Wellness Co. (WOOF) is one of the uglier names in retail. The bricks-and-mortar pet store chain is highly leveraged, relatively slow-growing, and has roughly 20% of its floated shares sold short. 

The company is also facing fears of AI displacement. AI agents make it easier for shoppers to compare online prices and buy from the lowest-cost supplier. That could hurt Petco’s e-commerce operations by forcing the retailer to drop prices at Petco.com. Shares are down 33% in a year, and 78% since ChatGPT was launched in 2022.  

Of course, concerns that chatbots will replace shopping websites aren’t limited to Petco. Online rival Chewy Inc. (CHWY) has fallen 38% in the past year – even more than Petco’s decline. 

However, Petco is making moves to avoid getting further displaced by AI and other tech. First of all, the firm never had a particularly strong internet strategy for chatbots to displace. Analysts believe that just 15% of Petco’s sales come from its e-commerce website – significantly below the 21% to 25% range that other brick-and-mortar names like Target Corp. (TGT) and Walmart Inc. (WMT) command. In addition, Petco has moved toward in-person services at its stores, such as vet care and grooming. These services are far harder for digital chatbots to replace. 

Moreover, Petco is using – applying – AI to make improvements to its finances.  

For instance, Petco began using AI tech from a company called Constructor in 2024 to help predict what its online shoppers would buy. Digital conversions rose 13%. Then in February 2026, Petco selected a new AI-powered merchandising system to help improve sourcing and planning to help cut costs and stock its stores with better-selling products. 

The results have been promising so far. At a September 14 investor conference, CEO Joel Anderson said, “We’re already starting to see efficiency, especially in customer service and chat.” He expects AI to play an even larger role in 2027 as the technology improves. 

These AI benefits are also starting to show up in financial results. Earnings per share are expected to jump 20% this year to $0.23, and to rise another 10% next fiscal year. That will allow Petco to use its profits to pay down roughly $150 million per year in debt, adding roughly $0.45 per year to stock values. 

So, even if the company does nothing from here, shares will be worth 18% more per year simply by converting debt back into equity. Strangely enough, AI could make Petco’s stock worth $4 per share or more. 

Stock to Buy No. 3: The Energy Play 

Last week, reports surfaced that Amazon.com Inc. (AMZN) was buying billions of dollars of Nvidia Corp. (NVDA) chips with no way to power them.  

Internal emails showed Amazon expected to receive $5 billion worth of Nvidia AI server systems in August, followed by $3 billion more each following month – and many of the chips had nowhere to get plugged in. 

Amazon joins a host of other data center companies that are facing electricity constraints. In fact, a recent study by Goldman Sachs estimates that 40% of all 2026 data center projects will get delayed into 2027 from a lack of electricity. 

That’s why I want to reiterate one energy stock that I recommended here back in September: 

Transocean Ltd. (RIG). 

As I wrote then, the company is the world’s largest leaser of “floater” oil rigs (27 vessels) and owns another seven harsh-environment semisubmersibles. These platforms are used when ocean water is too deep to anchor regular rigs into the seabed.  

Business is booming. 

Energy companies are now looking beyond the Middle East for new sources of hydrocarbons. And they’re finding it in offshore fields in Brazil, West Africa, the Gulf of America, and more.  

They are now turning to companies like Transocean to supply the drilling rigs for these ultra-deep sites. 

 Transocean has already seen revenues surge 40% in the past two years. No new drillships have been ordered since 2014, and a previously oversupplied market is now swinging into deficit. Industry analysts believe that high-end floaters have been fully contracted through late 2027, allowing Transocean to charge fat premiums for renting its ships and achieve utilization rates “well into the 90s,” according to its CEO.  

Shares are already up 12% since I recommended Transocean on September 27. But the prospect of the AI Separation makes it an even more compelling stock. After all, the bankrupt railroads of the 1890s still needed fuel to deliver Richard Sears’ goods; AI data centers will find themselves in the same situation. 

The Other Side of the Separation 

The three stocks above are the “buy” side of the AI Separation. But every separation has two halves, and the “sell” part is worth watching too. 

Consider Oracle Corp. (ORCL). Last November, Eric told his readers to exit their positions. At the time, the data center company was one of the most celebrated AI stocks on Wall Street. Oracle was inking 12-figure AI deals, including the ambitious $500 billion Stargate Project with OpenAI and SoftBank. 

Eric saw something else. 

He saw an increasingly indebted firm borrowing money for projects that had no guarantee of paying off. Worst of all, half of Oracle’s future business depended on a single profitless customer, OpenAI. 

Oracle shares have since fallen more than 30%, and its bonds have been downgraded to one notch above junk. 

That’s the Builder side of the AI Separation. These companies are acting like the railway magnates of the late 1800s: borrowing enormous sums of cash to build infrastructure that no one is sure will all be needed. 

Plus, he also shows us his No. 1 AI Applier, including its name and ticker symbol. You don’t need to buy anything to get that recommendation.  

Click here to watch Eric’s new presentation and get his No. 1 AI Applier stock pick for free. 

I’ll see you back here next Sunday. 

Thomas Yeung, CFA 

Market Analyst, InvestorPlace 

Thomas Yeung is a market analyst and portfolio manager of the Omnia Portfolio, the highest-tier subscription at InvestorPlace. He is the former editor of Tom Yeung’s Profit & Protection, a free e-letter about investing to profit in good times and protecting gains during the bad.

The post 3 Stocks to Buy as the AI Trade Sputters  appeared first on InvestorPlace.

Today, you could make that trip in about 45 hours of driving time, or about 4-5 days depending on how much you chose to drive each day.

But Eisenhower wasn’t driving on modern highways. He was part of a military convoy attempting to cross the country on roads that were not always worthy of the name.

Vehicles frequently broke down; the convoy broke and repaired dozens of wooden bridges and reported that nearly all roadways were unpaved from Illinois through Nevada.

The trip took 56 days and left a lasting impression on the young officer.

It’s no surprise then that when Eisenhower became President, he championed the effort to build the Interstate Highway System.

That infrastructure buildout changed America.          

As it continued, goods began moving across the country faster and more efficiently. Businesses started reaching customers hundreds or even thousands of miles away. Entire industries grew around the new network of roads.

Seventy years after Eisenhower signed the Federal-Aid Highway Act of 1956, the Interstate Highway System has generated more than $6 in economic activity for every dollar spent on its construction, according to the American Society of Civil Engineers.

And a huge chunk of that wealth didn’t go to the companies building the highways.

Major freight haulers and companies such as FedEx (FDX) and UPS (UPS) have been huge beneficiaries of the ease of travel.

Many major businesses generate substantial revenue by locating their operations along highways. It could be McDonald’s (MCD), Waffle House, or Cracker Barrel. And if you’ve made a major cross-country road trip, maybe you’ve stayed in a Motel 6 or Holiday Inn.  

None of these companies built the infrastructure – but they capitalized on it, building huge businesses.

And we’re seeing something similar happening in America today.

The Next Great AI Companies

Companies like Microsoft (MSFT), Amazon (AMZN), Alphabet (GOOG) and Meta (META) have spent billions on AI infrastructure. They’ve built enormous data centers, bought countless computer chips and worked to secure enough electricity to run it all.

Wall Street traders have rewarded these companies with extraordinary market gains.

But are we forgetting the lessons about who grows rich from infrastructure buildouts? What if the next great fortunes are going to come from the companies that figure out how to use it to their best advantage?

Those are the companies Eric Fry is looking for. And he has a great history of finding them.

Eric is an expert global macro investor – that means he follows the world’s biggest trends and then homes in on the few companies best positioned to profit from them.

And he has seen this type of opportunity before.

Back in 2000, investors were pouring billions into the companies building the internet.

Telecommunications companies were laying millions of miles of fiber-optic cable. Technology stocks were soaring. And Wall Street couldn’t get enough of the companies making it all possible.

But while companies like Cisco and Corning were soaring, Eric recognized something most investors were missing. Many of the companies building the internet were borrowing enormous sums to build infrastructure that was rapidly becoming cheaper to use.

That’s when Eric started to look elsewhere.

One of the companies he found was Humana (HUM).

Yes, the health insurance company.

Its stock had fallen 59% from its previous high. But behind the scenes, Humana was using the internet to streamline claims processing, reduce administrative costs and improve its business.

Wall Street was largely ignoring it, but Eric wasn’t.

He recommended Humana to his readers. Over the next five years, the stock gained more than 350% and eventually rose roughly 4,000%.

Meanwhile, Cisco (CSCO), one of the great infrastructure stocks of the internet boom, collapsed nearly 90%.

Eric didn’t predict the end of the internet. But he did recognize that the next great winners might not be the companies everyone was watching.

And now he believes history is about to repeat itself with AI.

In fact, Eric believes we’re at a turning point in the AI boom.

He calls it “The Separation Phase.”

It’s when the companies that built the infrastructure begin to lose their advantage… and a new group of winners emerges.

Eric calls these companies “AI Appliers.”

They’re not necessarily technology companies. In fact, some of them operate in industries you’d never associate with artificial intelligence.

But they’re using AI to transform their businesses, cut costs and potentially generate extraordinary profits.

And Eric believes some of these overlooked companies could double in value over the next 12 months.

More importantly, he believes the shift could begin as soon as November 4 – the morning after the midterm elections.

That’s why he’s just recorded an urgent new presentation explaining what he sees coming, why some of America’s most popular AI stocks could be vulnerable, and where he believes investors should look instead.

He’ll also reveal how his Apogee system is identifying these opportunities — and give you the name and ticker symbol of one AI Applier he’s recommending right now.

Click here to watch Eric’s AI briefing — and discover the next generation of potential AI winners.

Enjoy your weekend

Luis Hernandez

Editor in Chief, InvestorPlace

The post The Biggest AI Winners May Not Be AI Stocks appeared first on InvestorPlace.

So researchers at the University of Chicago brought AI into their workflow to remedy this blindspot.

By building a map of 20 million biomedical papers and the 9 million researchers who authored them, they produced a mountain of research that could find new connections that change how we treat diseases.

Their system traces where scientists concentrate their attention. Then it searches in the opposite direction: the overlooked territory between established fields, where useful connections may be waiting.

The resulting ideas were dubbed “alien hypotheses.” In other words, they’re possibilities that fall outside the research paths humans tend to follow.

That is incredible! AI gives scientists a way to search for connections (that could otherwise never be found) systematically, and bring them into the laboratory for testing.

Meanwhile, another research team is attacking a different bottleneck: time.

Global climate simulations can occupy supercomputers for weeks. That limits how many scenarios scientists can examine as they study a changing planet.

Researchers at UC San Diego and the Allen Institute for AI have developed Spherical DYffusion, a model that simulates 100 years of global climate patterns in 25 hours. By combining generative AI with physics-based data, it runs roughly 25 times faster than the methods used for comparison, without requiring massive supercomputers.

A century of simulated climate. About a day of computing.

Now put those developments next to the conversation on Wall Street.

Investors are questioning whether the AI build-out can earn back its enormous cost. That is a necessary question. But the answer depends partly on applications still moving from research labs into practical use.

These projects show why the demand story extends well beyond writing emails and answering chatbot questions.

They do not guarantee profits. A hypothesis still needs an experiment. A climate simulation still needs validation. And an AI infrastructure company still needs customers who can pay.

But the range of problems AI can tackle is expanding while investors are reassessing what that capability is worth.

That tension is central to our latest episode of Being Exponential. We examine whether the sell-off reflects weakening demand, where I see opportunity, and the concrete warning signs that would change my bullish outlook.

Watch the full conversation by clicking the image below:

As we discuss in the episode, Anthropic’s growth decelerates while OpenAI gains momentum. My interpretation is that competition explains much of that divergence: Customers have more models and coding tools to choose from.

Measure the market before declaring that demand has disappeared. One company losing momentum can coexist with an industry gaining customers.

Then there is financing.

Building data centers requires enormous upfront spending. Servers arrive before years of customer payments do. Borrowing costs, construction delays, and access to capital all affect whether a project earns an attractive return.

S&P Global Ratings projects that combined hyperscaler capital expenditures will exceed $1.3 trillion in 2027, with external financing playing an increasingly important role. These are legitimate business risks.

But different companies carry different risks.

In the episode, I explain why concerns surrounding CoreWeave (CRWV) do not automatically justify the same conclusion about Nebius Group (NBIS), IREN (IREN), or Applied Digital (APLD).

You need to examine each company’s debt, funding arrangements, customer commitments, and ability to bring capacity online. A crowded customer pipeline does not eliminate financing risk. An expensive loan does not prove customers have stopped buying.

Networking remains a major focus, including Astera Labs (ALAB) and Marvell Technology (MRVL). As AI systems expand, moving data between processors becomes increasingly important. Buying more computing power accomplishes less if those processors spend too much time waiting for information.

Memory is another area to watch, including Micron Technology (MU) and SanDisk (SNDK).

Here, investors need to interrogate the earnings forecast. A low valuation can signal opportunity, but it can also reflect expectations that profits are approaching a cyclical peak. The next reports need to show whether demand and earnings strength can endure.

So, what changes my mind?

A meaningful slowdown across the major AI developers. Suppliers missing sales expectations and lowering forecasts. And, especially, the largest cloud companies cutting their capital spending plans.

That is why the spending outlooks from Meta Platforms (META), Amazon (AMZN), Alphabet (GOOGL), and Microsoft (MSFT) deserve your attention.

Maintained or increased budgets support the infrastructure thesis. Meaningful cuts require a reassessment.

Be a disciplined investor. Follow the evidence, and stay flexible when it changes.

My bullish case rests on expanding demand and continued investment. Earnings season gives us another opportunity to test both. The full episode walks through the setups I find attractive… and the warning signs I refuse to ignore.

P.S. My colleague Eric Fry sees a different risk emerging: a widening divide between companies spending heavily to build AI and businesses using it to improve their operations. He believes the midterm elections could accelerate that “Separation,” with Nov. 4 as a potential turning point. In his new briefing, Eric explains his case and reveals one AI stock he recommends — free. If you own AI stocks, his argument is worth understanding.

The post Why AI Stocks Are Falling (And What to Buy Now) appeared first on InvestorPlace.

A hurricane, a cold front and a nor’easter.

Waves reached heights of 100 feet. Winds roared past 80 knots. Meteorologists later said a convergence like this only happens once every 50 to 100 years.

Caught in the middle was the Andrea Gail, a commercial fishing boat that had set sail from Gloucester, Massachusetts, weeks earlier. Tragically, the vessel and its six crew members were lost at sea.

The disaster inspired the bestselling book and blockbuster movie The Perfect Storm, which helped popularize the expression we still use today to describe several powerful forces converging at once.

Of course, the stakes are very different when we’re talking about the stock market. But I believe a convergence of forces is developing that could create a remarkable opportunity for investors.

Specifically, I see five separate catalysts coming together between now and year-end that could help propel fundamentally superior small-cap stocks higher.

In today’s Market 360, I’ll walk you through those five catalysts, explain why smaller companies could be among the biggest beneficiaries. I’ll also show you how my Precursor Intelligence system can help identify potential winners before the rest of Wall Street catches on.

Catalyst #1: Third-Quarter Earnings Season Is Just Getting Started

The earnings party is just getting started. This is the catalyst I’m watching most closely.

According to FactSet, Wall Street now expects S&P 500 earnings to grow 29% from a year ago, compared with the 26.7% growth expected when the quarter began. That 29% figure combines results already reported with estimates for companies still to come. And since we know that companies have a habit of positive earnings surprises, it could be even higher. Either way, this would be the third straight quarter of earnings growth above 25%.

What’s especially encouraging is that analysts raised their earnings estimates during the quarter. That’s unusual, as analysts typically lower estimates as the quarter progresses. But this is the second quarter in a row that they’ve raised them.

Companies have also been more upbeat than usual. Among those issuing third-quarter earnings guidance, 62% provided outlooks above analysts’ expectations, compared with a five-year average of 40%.

And while the size of early earnings surprises has been smaller than usual, 84% of companies that have reported so far have beaten earnings estimates.

But here’s what really catches my attention.

Royce Investment Partners found that analysts expect earnings growth for small-cap companies to exceed that of larger companies in both 2026 and 2027.

That’s an encouraging sign that the next wave of earnings growth could extend beyond the big-name stocks that have dominated the headlines.

A smaller company that increases sales while keeping its costs under control can grow profits much faster than revenue. Factory overhead and other fixed expenses do not have to rise with every additional order. More of the next sales dollar can reach the bottom line.

Of course, a big percentage increase can also reflect a rebound from weak profits. That’s why I still want to see strong sales, expanding operating margins and healthy cash flow supporting the earnings growth. Management’s outlook for the next quarter matters, too.

So, as third-quarter earnings season gathers speed, I expect companies with the strongest fundamentals and most encouraging guidance to stand out.

Catalyst #2: A Likely Pause in Interest Rates

The Federal Reserve may give small caps some breathing room at its October meeting.

September’s employment report showed just 29,000 new jobs, and the unemployment rate stood at 4.2%. July and August payrolls were also revised down by a combined 60,000.

Those numbers suggest the Fed has good reason to pause and assess the impact of September’s rate hike.

Meanwhile, the inflation picture is mixed.

The Consumer Price Index (CPI) rose 0.6% in September and 3.7% over the past year.

The Producer Price Index (PPI) was even hotter, jumping 1.3% for the month and 6.3% over the past year.

The culprit: Skyrocketing energy prices.

So, the Fed still has some work to do. But with the labor market cooling, policymakers may be reluctant to raise rates again so soon.

The market seems to agree with my opinion, too. The Fed announces its next decision on October 28. The consensus is that an October rate hike is off the table.

That’s particularly important for small caps.

Smaller companies tend to be more sensitive to changes in interest rates. That’s because they often rely more heavily on floating-rate loans and outside financing than larger companies do.

Consider a company with $100 million in floating-rate debt. If its borrowing rate rises another quarter of a percentage point, that adds $250,000 to the annual interest bill.

That’s why I look for small companies with manageable debt and enough sales and profit growth to carry their financing costs. Continued growth alongside a more patient Fed would give those businesses a better chance to deliver.

Catalyst #3: Greater Clarity After the Midterms

The November 3 midterm elections will remove another obstacle for the market – uncertainty about the direction of Washington.

As the results become clear, businesses and investors should have a better idea of what to expect on taxes, regulation and federal spending. That can make it easier to evaluate an investment or move forward with an expansion.

There is a favorable historical pattern here – especially for smaller companies.

The Russell 2000 has gained an average of 6.2% over the 60 trading sessions following midterm elections since 1982. Small caps posted positive returns during that stretch in eight of the 11 periods studied.

Now, an election does not, by itself, eliminate a company’s financing costs or create demand for its products. You still need the economic and earnings backdrop to be there.

But on that front, there is encouraging news.

The government’s latest estimate showed that inflation-adjusted consumer spending and private fixed investment grew at a 4.6% annualized pace in the second quarter. That measure captures spending within the private U.S. economy, including investment in equipment, buildings and housing.

That matters to smaller businesses supplying equipment, serving local customers and building new construction projects.

My view is that greater clarity in Washington could help investors refocus on companies already turning that domestic demand into higher profits.

But here’s the important thing to remember.

If Democrats get control of the House or the Senate or even both, President Trump has already frontloaded his economic agenda.

Either way, we will likely have a divided government. History shows that’s generally good for stocks.

Catalyst #4: A Second Russell Reconstitution

Small-cap investors have another date to watch this year: December 11.

That’s when FTSE Russell’s first December reconstitution in more than 30 years takes effect after the market closes.

For decades, the Russell indexes have undergone a major reshuffling just once a year, in June. Starting in 2026, that process will happen twice a year.

Here’s why it matters.

Russell ranks publicly traded companies by market capitalization. The largest 1,000 go into the Russell 1000, while the next 2,000 make up the Russell 2000 small-cap index.

When a company enters one of these indexes, the funds that track it must adjust their holdings. That can create significant buying pressure in newly added stocks.

And when billions of dollars move at the same time, the market notices.

The reconstitution is also one of the few times each year when investors get a clear look at which companies are moving up in the ranks – and which are falling behind.

This year, those rankings matter more than usual.

This comes at a particularly interesting time because it could coincide with both stronger earnings growth and seasonal buying in small-cap stocks.

I’ve seen firsthand how powerful these shifts can be.

Take Power Solutions International, Inc. (PSIX) for example. I recommended it to my Accelerated Profits subscribers in January last year.

Power Solutions makes engines and power systems used in heavy equipment, commercial vehicles and backup power applications – and increasingly, in data centers.

At the time, it showed a history of posting big earnings surprises and increased analyst estimates. So, I had to make sure my subscribers could get in.

Five months later, it was added to the Russell 3000 during last year’s reconstitution. Once it became official, PSIX climbed 21% in the first week.

That’s a big move. All told, we ended up making 121% gain on PSIX by the time we sold it in May this year.

Now, index inclusion alone doesn’t guarantee a stock will surge. But when growing institutional demand meets strong sales and earnings, the results can be impressive.

And with another Russell reconstitution just weeks away, I’ll be watching closely for companies showing those same characteristics.

Catalyst #5: Seasonal Strength and an “Early January Effect”

The seasonal calendar is also about to become more favorable.

November begins the stock market’s historically stronger November-through-April stretch. Small caps have an additional pattern around the turn of the year: the tendency to outperform larger stocks known as the January effect.

Despite its name, that pattern can start before January.

In fact, December has historically been one of the most favorable months for smaller stocks.

There are a few reasons for this. But one of the most powerful is simply window dressing – where managers sell duds and buy stocks with good fundamentals to make their portfolios look “pretty.”

How I Find Tomorrow’s Market Leaders

With these five catalysts converging, the question is which small-cap stocks are best positioned to benefit.

That’s where my Precursor Intelligence (P.I.) system comes in.

P.I. analyzes roughly 6,000 stocks and ranks them based on eight fundamental signals and one quantitative money-flow signal.

Without a system like this, a stock like Power Solutions might not even be on the radar for most investors until after the buying pressure has already shown up.

That is why I recently put together a special presentation that shows you what my P.I. system is flagging right now. I explain how it works, why institutional buying matters and how you can use these signals to spot promising stocks before the rest of Wall Street catches on.

You can get the details and learn what P.I. is flagging today by clicking here.

Sincerely,

Louis Navellier

Editor, Market 360

The post 5 Catalysts Set to Spark a Small-Cap Rally Before Year-End appeared first on InvestorPlace.

Right now, he’s concerned about something happening beneath the stock market’s record highs. And he’s found an interesting opportunity far from the handful of technology stocks dominating the headlines.

He’s also recorded a free special presentation about what he believes could be a major turning point for AI investors beginning November 4. You can watch it here and get the name and ticker of his No. 1 AI stock pick, absolutely free.

But first, Eric has a few things to say about the market’s increasingly peculiar behavior.

Hello, Reader.

In October 2003, the Brian Jonestown Massacre released a song called “A New Low in Getting High.”

The California retro-rock band wasn’t singing about the stock market, of course. But it might as well have been writing the dot-com bubble’s epitaph.

In the months leading up to March 2000, when the Nasdaq Composite reached its dot-com peak, the index kept setting records… even as fewer and fewer stocks participated in the rally.

By the time the Nasdaq hit its high, plenty of stocks were already having a miserable time. Then the bubble burst.

Over the next two and a half years, the Nasdaq Composite plunged 78% from that peak, finally hitting bottom in October 2002.

And now we may be seeing something disturbingly similar.

I like to compare the stock market to a cocktail party. A healthy party has people mingling, laughing, and generally enjoying themselves. The more guests participating, the better the party.

But when a handful of guests are laughing in the corner while most of the room is plotting an escape, the festivities have taken an unpleasant turn.

Lately, that’s been the stock market.

Over the past 18 months, the Nasdaq-100 has closed at record highs 55 times. But during its three most recent record-setting days, an average of just 764 stocks across U.S. exchanges reached new 52-week highs.

A year earlier, that figure was 1,581.

The Nasdaq-100 keeps setting records, but fewer and fewer stocks are joining the celebration … a stat eerily close to the market before the dot-com bubble burst.

It’s worth asking what investors can do about it. After all, knowing that a party is going badly isn’t especially useful unless you know where the exits are, or where else you might want to spend the evening.

Today, I’ll show you why this market deserves caution — and give you the name of an overlooked healthcare stock that I believe offers substantial upside, even if the market’s party keeps shrinking.

The Music’s Still Playing, but Look at the Room

Take a look at the chart below.

The green line shows the Nasdaq-100, which has been marching steadily higher. Nothing terribly alarming there.

But the black line tells a very different story. It measures the number of stocks across U.S. exchanges hitting new 52-week highs, minus those falling to new 52-week lows, averaged over two weeks. When that line drops below zero, more stocks are hitting new lows than new highs.

And lately, it’s fallen off a cliff.

The Nasdaq-100 is setting records while hundreds more stocks are hitting new lows than new highs. That’s an unhealthy combination.

During the Nasdaq Composite’s final 34 record-high days before the dot-com crash, new lows outnumbered new highs on the New York Stock Exchange on 31 of those days.

I’m not suggesting we’re about to experience another 78% collapse. History rarely repeats itself quite so obligingly.

But I’ve been around long enough to know that when the market’s leaders keep climbing while the rest of the market deteriorates, trouble can follow.

One reason for this growing imbalance is what I call a self-fulfilling buying cycle. The market’s biggest companies attract an enormous amount of investment money. As their stocks rise, index funds and professional investors buy more of them. That additional buying pushes prices higher, which attracts still more money.

Meanwhile, smaller companies and less fashionable industries get left behind.

The popular stocks become more popular because they’re going up. The unpopular stocks become less popular because they aren’t. It’s a remarkably simple process, and one that can continue much longer than common sense might suggest.

Eventually, that concentration makes the entire market more vulnerable. If the handful of companies doing the heavy lifting stumble, there aren’t many others ready to pick up the slack.

My advice is simple: Don’t confuse a market hitting record highs with a market that’s getting stronger. And don’t assume the stocks everybody wants to own are necessarily the best investments available.

In fact, some of the most interesting opportunities may be hiding among the stocks Wall Street has stopped inviting to the party.

Which brings me to a company that’s about as far removed from Silicon Valley’s AI frenzy as you can get.

A Healthcare Giant Wall Street Has Left Off the Guest List

Novo Nordisk A/S (NVO), the Danish pharmaceutical giant behind Ozempic and Wegovy, used to be one of Wall Street’s favorite stocks.

Then its longtime rival, Eli Lilly & Co. (LLY), began winning the battle for the lucrative obesity-drug market. Lilly’s Zepbound delivered better weight-loss results than Novo’s injectable Wegovy in a landmark clinical trial, and investors responded accordingly.

Over the past five years, Lilly’s stock has gained roughly 400%, while Novo’s has lost ground.

Wall Street seems to have decided that Lilly has won the obesity-drug race, collected the trophy, and retired the competition. I think the victory celebration may be premature.

Novo currently trades at roughly 14 times earnings, compared with 34 times for Lilly. Its market capitalization is about one-fifth of Lilly’s, even though their obesity and diabetes businesses generate similar annual sales.

That’s a remarkable valuation gap between two companies competing in the same enormous market.

And here’s what Wall Street may be missing: Lilly may have won the battle of the injections, but Novo has taken an early lead in pills.

In January, Novo launched the first oral GLP-1 treatment for obesity, the Wegovy pill. During its first six months, it racked up approximately 5 million prescriptions, capturing roughly 76% of the U.S. oral obesity-drug market.

Lilly’s competing pill arrived in April but has yet to match that momentum.

The appeal of an effective obesity pill is obvious. Millions of patients would prefer swallowing a tablet to injecting themselves every week. And whichever company captures a meaningful share of that market could enjoy a very profitable future.

Novo also has a promising pipeline of new treatments, including its next-generation obesity drug CagriSema, along with therapies targeting blood disorders and liver disease.

And it’s putting AI to work through partnerships with Microsoft Corp. (MSFT), OpenAI, Amazon.com Inc. (AMZN), and other technology companies to accelerate drug discovery and improve its operations.

That’s what I call an AI Applier: an established business using AI to improve its profitability rather than spending billions building the infrastructure behind it.

Novo doesn’t need to invent the next generation of AI models. It simply needs to use them to develop better medicines, more efficiently.

Of course, Novo isn’t without risks. Lilly remains a formidable competitor, and Novo faces pricing pressure, patent expirations, and uncertain regulatory outcomes.

And cheap stocks have a habit of remaining cheap when the underlying business fails to improve. That’s why I never consider a low valuation, by itself, a compelling reason to buy.

But Novo is still a highly profitable pharmaceutical company with established products, a substantial research pipeline, and a potentially valuable head start in oral obesity treatments. Those are meaningful assets, even if Wall Street has temporarily lost its enthusiasm for them.

At the beginning of this year, I called Novo one of my “Top 7 Stocks for 2026.” At today’s prices, I believe Novo could potentially double and still trade at a discount to Lilly’s valuation. That outcome isn’t guaranteed, of course. But it illustrates just how much pessimism investors have already baked into Novo’s share price.

In a new special report, I explain a strategy that could produce even larger percentage gains if my forecast for Novo proves correct. It also involves greater risk than simply owning the shares. That report is one of the bonuses available to investors who take action after watching my new free presentation.

And Novo is just one of the opportunities I’ve been researching.

I believe an even bigger investment shift could begin around November 4, as the market starts distinguishing between companies spending enormous sums building AI infrastructure and those putting AI to profitable use.

I’ve recorded a free special presentation explaining what I’m seeing. During it, I’ll reveal the name and ticker of my No. 1 AI Applier, another company I believe is positioned to benefit from this shift.

Click here to watch my free presentation and discover my No. 1 AI Applier stock pick.

As for the stock market’s cocktail party, I’m not suggesting you leave just because a few guests have become obnoxiously loud.

But when most of the room is heading for the exits, it pays to notice.

And while the crowd continues to celebrate the same handful of fashionable stocks, I’ll keep looking for opportunities in the quieter corners of the market.

Regards,

Eric Fry

Senior Global Macro Analyst, InvestorPlace

P.S. Novo Nordisk is a good example of why Eric looks beyond the stocks getting all the attention. Wall Street has fallen in love with Lilly, but Eric believes investors may be overlooking an opportunity in its much less fashionable rival. And Novo is just one of the companies he’s watching as AI begins separating the winners from the losers. Watch Eric’s free presentation to learn why he believes that separation could accelerate beginning November 4 — and get the name and ticker of his No. 1 AI Applier, free.

The post One Overlooked Healthcare Stock That Could Double appeared first on InvestorPlace.

He’s helped revolutionize the auto industry, made reusable rockets a reality and built the world’s largest satellite internet network.

But last week, he showed off something straight out of a science-fiction movie.

A flying car.

On October 15, Musk unveiled a prototype of Tesla’s next-generation Roadster at a SpaceX testing facility in Texas.

The electric sports car raced up a curved ramp, drove upside down, then launched into the air before flipping over and landing safely on its wheels.

The secret? A combination of Tesla’s engineering and SpaceX’s rocket technology. A special suction system kept the Roadster attached to the ramp, while powerful thrusters released bursts of compressed gas to help it maneuver through the air and land safely.

So, was this a bold leap forward in automotive technology? Or was it an elaborate marketing stunt?

Yes.

If you’ve followed Elon Musk for any length of time, you know that’s often how things go.

He’s famous for making ambitious promises and generating enormous excitement around technologies that sometimes take years longer than expected to reach consumers.

Consider the Roadster itself. Musk first unveiled the second-generation model back in 2017, with production originally expected in 2020.

Here we are, nine years later, and it’s still not available to buy.

But there’s another side to that story.

Whatever you think of Musk’s timelines, you can’t deny that Musk has a habit of pushing innovation forward. And last week’s demonstration showed what can happen when Musk combines Tesla’s engineering expertise with the rocket technology developed by Space Exploration Technologies Corp. (SPCX).

Interestingly, the two companies may soon become even more closely connected.

Of course, before we start speculating about what the future might hold, I think it’s important to take a closer look at how both businesses are performing today.

So, in today’s Market 360, we’ll break down this week’s quarterly results from SpaceX and Tesla, Inc. (TSLA), discuss what a potential merger could mean – and talk about how investors can benefit from Musk’s ambitious plans without having to ride the roller coaster that often comes with owning his companies.

SpaceX’s Earnings Blast Past Expectations

Let’s start with SpaceX, which reported its third-quarter results on Tuesday. And the results were nothing short of spectacular.

Third-quarter revenue soared 161% year-over-year to $14.6 billion, easily topping analysts’ expectations for $12.8 billion.

Even better, SpaceX reported its first quarterly profit since going public earlier this year. Third-quarter earnings came in at $4.4 billion, or $0.35 per share, compared with a loss of $1.1 billion, or $0.36 per share, in the same quarter a year ago.

That also crushed analysts’ expectations for earnings of just $0.13 per share, resulting in a whopping 169.2% earnings surprise!

Now, what really caught my attention was the incredible growth in SpaceX’s artificial intelligence business.

The company’s AI division generated $7.6 billion in revenue during the quarter. That represents a whopping 830% increase from a year ago.

In fact, AI now accounts for more than half of SpaceX’s total revenue. So, it’s quickly becoming one of the company’s biggest growth engines.

And SpaceX’s Starlink satellite internet business isn’t slowing down, either.

Revenue from its Connectivity segment, which includes Starlink satellites and internet service, climbed 69% year-over-year to $5.2 billion, thanks to strong demand from consumers, businesses and government customers.

And Musk has even bigger ambitions for Starlink. Bloomberg reported Thursday that SpaceX is seeking access to at least 80,000 cell sites across the U.S. as it explores becoming the nation’s fourth major wireless carrier.

Clearly, SpaceX has a lot of momentum behind it right now. But there’s another number that caught my attention: $19.6 billion.

That’s how much SpaceX spent on capital expenditures in the third quarter alone, nearly three times what it spent a year ago. And roughly $16.4 billion of that went toward its AI business.

That’s an enormous investment. But it also shows just how aggressively the company is positioning itself for future growth.

The bottom line: SpaceX is no longer just a rocket company. It’s becoming a major force in the AI revolution, and its latest earnings results show just how quickly that business is growing. But it also underscores how much capital SpaceX needs to support its ambitious growth plans.

Tesla’s Earnings Beat Comes With a Catch

Now, let’s turn to Tesla, which reported its third-quarter results after the closing bell on Wednesday.

Unlike SpaceX, Tesla’s latest results were a bit of a mixed bag. But the company did manage to surprise Wall Street.

Third-quarter revenue came in at $28.05 billion, essentially flat compared to the same quarter a year ago. That also fell slightly short of analysts’ expectations for $28.13 billion.

Meanwhile, adjusted earnings slipped 4% year-over-year to $0.48 per share, compared with $0.50 per share, a year ago. The good news is that earnings still topped analysts’ expectations for $0.44 per share, resulting in a 9.1% earnings surprise.

Now, the real bright spot was Tesla’s cash flow.

The company generated $1.53 billion in positive free cash flow during the third quarter. That was a pleasant surprise, considering analysts expected Tesla to burn through $4.92 billion in cash. However, free cash flow was still down 62% from a year ago.

Tesla also managed to keep its capital expenditures below Wall Street’s estimates. The company spent $4.73 billion during the quarter, compared with forecasts for nearly $8 billion.

That’s still more than double what Tesla spent a year ago. But spending came in well below Wall Street’s expectations. In fact, Tesla now expects to spend about $20 billion in capital expenditures this year, down from its previous forecast for more than $25 billion.

Of course, Musk still has some big plans for Tesla’s AI business.

The company recently started production of its Optimus humanoid robots at its Fremont factory. And active Full Self-Driving subscriptions surged 67% year-over-year to 1.74 million during the quarter.

That’s encouraging progress, especially as Tesla looks to expand beyond its traditional electric vehicle business.

There are some encouraging signs here, especially Tesla’s improving automotive margins and stronger-than-expected cash flow. But with revenue essentially flat and profits declining, the company still has plenty to prove.

But investors clearly wanted more. Tesla shares fell by about 3% Thursday as Wall Street weighed the company’s weaker profits against its ambitious plans for robotics and autonomous driving.

The Bigger Opportunity Behind Musk’s AI Ambitions

This brings me back to the possibility of SpaceX and Tesla joining forces.

During SpaceX’s earnings call Tuesday, Musk confirmed that both companies have formed independent committees to explore a potential merger. While no agreement has been reached, Musk said he sees real advantages to combining the businesses.

It’s easy to understand why.

SpaceX has already become a major force in AI, while Tesla continues to invest in autonomous driving and robotics.

The two companies are already working together on Terafab, an ambitious semiconductor manufacturing project in Texas designed to produce advanced AI chips for everything from Tesla’s humanoid robots to SpaceX’s space-based data centers. Musk said Tuesday that he hopes to begin large-scale production by 2028.

By combining their technologies and resources, the two companies could give Musk a significant advantage in the race to develop the next generation of AI.

But whether they merge or not, I believe Musk’s biggest breakthroughs are still ahead of us.

And the opportunities could extend far beyond his companies.

Folks, we’re still in the early stages of this revolution. As AI becomes more powerful, it could help scientists develop new treatments for deadly diseases, unlock advances in energy and quantum computing, transform space exploration and change how we live and work every day.

Of course, making all this possible will require enormous investments in computing power, advanced chips, energy and other essential infrastructure.

And that’s where I think investors should be looking.

You see, I’ve never been one to chase a stock simply because its founder has an exciting vision. I want to see strong sales growth, accelerating earnings and improving fundamentals. That’s why I’ve generally preferred other opportunities over Tesla and SpaceX.

But those billions Musk is spending aren’t simply disappearing. They’re flowing to the companies supplying the technology and infrastructure needed to bring his vision to life.

And I believe some of those companies offer a much more attractive way to invest in the next phase of the AI Revolution.

In fact, I’ve been studying one of Musk’s most ambitious AI initiatives, and I’ve identified three companies outside his business empire that could be among the biggest beneficiaries.

That’s why I’ve put together a special video presentation to share what I’ve uncovered.

During this exclusive briefing, I’ll also show you the technology in action so you can see why I’m so excited about its potential. I’ll also explain why I believe it could trigger a new wave of investment opportunities – and reveal details about the three stocks positioned to benefit.

You can watch my special presentation right here.

Sincerely,

Louis Navellier

Editor, Market 360

The post Tesla and SpaceX Could Merge. But Here’s the Bigger Opportunity… appeared first on InvestorPlace.

This week, in Brussels, the European Union unveiled a sweeping new Arctic strategy featuring two flagship projects: 

Because, as EU foreign policy chief Kaja Kallas put it, “Arctic security is European security.”

That same day, at Cape Canaveral, the U.S. Air Force Research Laboratory loaded military-style cargo pods – survival gear, medical equipment, trackers – onto a SpaceX (SPCX) rocket and flew them to orbit and back. The test is part of a program studying whether rockets could someday deliver supplies to troops anywhere on Earth within hours.

Two bureaucracies that rarely agree on anything have, in effect, issued the same memo: space operations are essential. Now governments are spending to guarantee access on their own terms.

A sovereign space system lets a country launch its own payloads, communicate securely, monitor threats, move supplies, and keep operating through a crisis.

For years, that was a think-tank concept. This month, it became a budget line. And that means it’s time for investors to start paying closer attention.

Europe Is Building Sovereign Space Infrastructure

We’ll start with the Arctic because the region is becoming a bona fide arena of competition.

Melting ice is opening shipping lanes and mineral access. Russia has merged its Baltic and Arctic fleets, and undersea cables keep suffering mysterious “accidents.” 

Europe’s response is telling. Its new strategy calls for the region’s own secure satellite constellation over the region, its own cable routes, and a new hub to watch over the infrastructure it already has.

The roughly 350-satellite constellation the EU is building is, in part, an alternative to Starlink – and coverage of the Arctic strategy made clear that several measures aim to reduce dependence on the United States, too.

Ukraine Shows the Risk of Depending on Someone Else’s Network

It seems Europe has internalized a hard lesson over the past few years: connectivity becomes a national-security asset the moment somebody else controls the switch. Just ask Kyiv. Ukraine’s war effort has run on Starlink since 2022 – and this month delivered the starkest reminder yet of who really controls it. On Oct. 14, Ukrainian forces found their Starlink and Starshield terminals throttled without warning. Anything moving faster than roughly 100 mph – drones, aircraft – lost its connection, right as tensions between Washington and Kyiv were boiling over. Zelensky says identical terminals outside Ukraine kept working at those speeds, which is why Ukrainian officials believe the limits were aimed squarely at them. 

Who gave the order is still in dispute. Musk says the U.S. military sets usage limits, the White House denies involvement, press reports point in both directions, and senators from both parties want an investigation. Either way, the lesson landed in Kyiv with full force: somebody else’s hand is on the dial.

Defense officials the world over watched that episode unfold. Which is why sovereignty spending is structurally different from commercial demand. It doesn’t shrink when GDP dips or a hyperscaler trims its budget. Its entire purpose is to exist regardless of what anyone else does.

America Is Running Into a Space Launch Capacity Bottleneck

Now, the United States has the opposite problem. It doesn’t lack a space champion – it lacks room on the runway.

Cape Canaveral and Vandenberg, the nation’s two great launch ranges, are running out of capacity as national-security launches and commercial missions surge. Congress has already allocated $1.3 billion for range construction through 2028, and the Space Force’s next budget request seeks another $2.2 billion for launch infrastructure on top of it. 

The service awarded a contract worth up to $4 billion to modernize operations at both ranges into the next decade. And a congressionally mandated study just concluded the country likely needs an entirely new third spaceport capable of heavy and super-heavy launch – with a capability goal of 2030 that Space Force leadership itself calls aspirational.

In other words, the Pentagon is treating launch capacity the way it treats shipyards and runways: as strategic infrastructure that cannot be allowed to bottleneck. 

The Pentagon Is Testing Space-Based Military Logistics

Which brings us back to that cargo test at the Cape.

The capsule involved – SpaceX’s Starfall – is a squat, disk-shaped reentry vehicle about 10 feet across, built to bring roughly a metric ton of payload back from orbit. SpaceX publicly emphasizes microgravity manufacturing and research returns. But the Air Force’s interest points somewhere else entirely. Its Rocket Cargo program is studying whether large commercial rockets could deliver matériel anywhere on the globe on tactical timelines – to contested areas, disaster zones, or places aircraft can’t easily reach. 

The program’s partner list runs from SpaceX and Blue Origin to Rocket Lab (RKLB), Sierra Space, and Anduril. And the Air Force already holds a contract with SpaceX to demonstrate delivering a transport plane’s worth of supplies anywhere on Earth in under 90 minutes using Starship.

None of this means ammo crates will be falling from the sky next year. Starfall is not a military delivery service today. This week’s test was about collecting data, not dropping supplies to troops. But the direction is clear – because putting assets overhead is only half the job. Keeping them fueled, repaired, and replaceable is the other half. And that’s the half the Pentagon just started rehearsing.

Meanwhile, aboard the International Space Station, astronauts are testing spacesuits, running lunar-agriculture experiments, and studying how human lungs behave in microgravity. Unglamorous stuff – yet no nation maintains a durable presence anywhere, on Earth or off it, without food, suits, medicine, and life support.

Once you put all the layers together, the architecture comes into focus. Launch establishes access. Communications create control. Logistics keep the system supplied. Life support makes it permanent. That’s the full stack of space sovereignty – and every layer of it is being funded, right now, across the globe.

Space Stocks Positioned Around the Sovereignty Buildout

Here’s the throughline for investors. Every sovereign space program, whatever flag it flies, has to buy the same two things: hardware that survives in orbit, and the earthbound industrial base that launches, controls, and replaces it. Own the companies selling those, and you’re effectively collecting from every program at once.

A handful of public companies sit directly in that flow:

• Rocket Lab (RKLB) is the closest thing to a one-stop supplier outside SpaceX itself: launch vehicles, spacecraft platforms, and components that let governments avoid betting everything on a single provider – plus a seat in the Air Force’s orbital-logistics research. Its Neutron rocket is aimed squarely at the national-security launch market everyone just agreed is capacity-constrained.
• Redwire (RDW) supplies the power systems, structures, and mission hardware that sovereign satellites and stations are built from – picks and shovels for anyone, government or private, that wants a presence in orbit.
• Planet Labs (PL) and BlackSky (BKSY) sell what every government in this story ultimately wants – persistent, independent eyes on Earth. Watching infrastructure, borders, and fleets without relying on another nation’s intelligence is sovereignty in its purest form.
• Amentum (AMTM) is an under-the-radar ground play. Through its Jacobs Technology unit, it holds the Space Force Range Contract – worth up to $4 billion through 2035 – to modernize and run the Eastern and Western ranges. If America builds more launch capacity, somebody has to engineer, maintain, and operate it. 

Several of these plays are volatile small caps, and government procurement moves in lurches. 

But the demand behind them is now being written into national strategies, on multiple continents, with security justifications that outlast any single budget cycle.

The Bottom Line: Governments Are Paying for Control

Flags and footprints decided the last space race. Budgets and supply lines will decide this one. 

Europe is buying sovereign communications. America is buying sovereign launch capacity and testing sovereign logistics. Both are spending like nations that believe access to orbit sits in the same category as access to oil, chips, and electricity: too important to rent.

But run back through everything we’ve discussed and count how often one company appears. 

The rocket that flew the Air Force’s cargo test…

The constellation Europe is spending billions to avoid depending on…

The launch cadence overwhelming America’s ranges…

The Starship contract to deliver cargo anywhere on Earth in 90 minutes…

Governments on two continents are reorganizing budgets around capabilities that, today, largely exist inside Elon Musk’s empire – racing either to buy from it or to build around it. Either way, the spending flows toward the same map of hardware, suppliers, and chokepoints.

I’ve spent months charting that map as part of a research project I call “XPANSE“ – the full blueprint of what Musk is assembling, the constraints it has to break, and, most importantly for us, the publicly traded suppliers positioned at its hardest bottlenecks. 

In my briefing, I walk through the three steps I believe investors should take now, and I give away the name and ticker symbol of one company sitting at the center of it all – for free.

The era of space sovereignty has a dozen governments as customers and one indispensable vendor. You can guess which side of that arrangement the profits favor.

Watch the full XPANSE briefing now to learn everything I know.

The post The New Space Race Is About Who Controls the Infrastructure appeared first on InvestorPlace.

Last night, Meta Platforms (META) reported solid third-quarter earnings – and got punished for it.

Revenue jumped 26% to $64.6 billion, beating estimates. Excluding a one-time $9.9 billion legal charge, earnings came in at $7.40 per share, well above the $6.54 consensus.

Wall Street didn’t care.

As I write on Thursday, Meta is down more than 6%, the Nasdaq 100 is off 2.5%, and many AI darlings are down double digits. To be fair, Meta isn’t the only issue. Adding to the gloom are Tesla (TSLA), which also reported last night and cut its spending outlook, as well as Lam Research (LRCX), which issued disappointing guidance.

Returning to Meta, the problem isn’t what it’s earning – it’s how it’s paying for AI.

In Q3, Meta’s capex ate up more than all the cash its business generated, for the first time since 2012. Free cash flow turned negative, to –$2.1 billion. And Meta now carries more debt ($83.7 billion) than cash and securities ($82.4 billion).

That’s on top of $55 billion in bonds sold over the past year, plus roughly $40 billion in off-balance-sheet data center financing. And last night, Meta created a new class of non-voting stock that it says will be available for “capital raising.”

Bond investors noticed. Bloomberg reports that Meta’s credit risk hit a record high today on fears that tech giants will issue more debt to fund the AI buildout.

As our technology expert Luke Lango, editor of Innovation Investor, reminded us in yesterday’s Digest, “Bond markets tend to sniff out trouble before stock markets do.”

To be clear, Meta is not CoreWeave (CRWV) – the credit risk example we cited yesterday. It’s still enormously profitable. But when one of the world’s richest companies turns to borrowed money and new stock to fund its AI ambitions, it raises today’s question…

If AI busts, does it take the rest of your portfolio with it?

Yesterday’s Digest tackled two questions…

Luke’s Peak Watch Checklist addressed when the AI boom might turn. And our global macro expert Eric Fry’s “Separation” framework addressed who gets hurt (the AI Builders) and who survives (the AI Appliers).

But there’s a third question that matters to every investor…

How bad could an AI bust get?

Would it be just a tech-sector problem? Or might it drag down the whole market, and the non-AI part of your portfolio, along with it?

History points toward both outcomes, sometimes within the same bust.

When the Nasdaq peaked in March 2000, plenty of investors did exactly what you’d expect. They rotated out of tech and into unglamorous “old economy” stocks.

For a while, it worked beautifully. In 2000, the Nasdaq lost 39%, its worst year since its creation in 1971. Meanwhile, the Russell 1000 Value index, a basket of large, unexciting companies, gained 7%. Small-cap value stocks jumped nearly 23%.

That was a tech bust. It was brutal for tech investors, but it was contained.

But then it spread…

The damage leaked into the broader economy, helped along by a mountain of telecom debt, and the U.S. slid into recession in 2001. At that point, there was nowhere to hide.

Consider The Home Depot (HD) – the opposite of an internet company, selling lumber, paint, and power drills.

On the last trading day of 1999, it closed at a record $68.75. By the end of 2002, it had fallen to roughly $21, making it the Dow’s worst performer that year with a 53% drop. Home Depot’s own stumbles played a role, but the recession hammered its results. The stock didn’t revisit its 1999 high for nearly 13 years.

So, the question that matters for your non-AI holdings isn’t simply whether the AI boom ends. It’s whether an AI bust stays contained, as in 2000, or spreads, as in 2002.

The answer depends on what kind of bust it is.

To help us navigate this, let’s turn to Tom Yeung, Eric’s lead analyst at The Speculator. In his Tuesday update, Tom dissected the anatomy of a tech bust and where AI fits.

Not all busts are created equal

Tom’s key insight is that busts come in three distinct flavors, which he ranked from least to most destructive.

The first is the platform bust. A dominant company funds its expansion with its own cash and thrives, while speculation and carnage occur on the periphery.

Think Apple (AAPL) during the smartphone revolution. It became the most valuable company on Earth, while some of its chip suppliers lost half their value and one glass supplier went bankrupt.

The second is the industry-wide bust. Money floods a sector, and the losses spread throughout it, but the broader economy is spared.

Here’s Tom to illustrate:

Automobiles are the classic example. The number of U.S. automakers shrank from roughly 272 in 1909 to nine by 1941, wiping out large swaths of investor wealth without triggering a broader economic collapse. 

Tom also points toward busts in airlines (1920s and 1980s), video games (early 1980s), PCs (mid-1980s), solar (2008-2013), and shale (2014-2016). 

The third is the economy-wide bust – the Home Depot scenario. Here, the buildout is financed with too much borrowed money, and the losses spread far beyond the technology itself.

Tom highlights a few examples: the railroad panics of 1873 and 1893 triggered bank failures and some of the longest recessions in U.S. history… leveraged speculation in radio and utilities helped trigger the Great Depression… and the debt-fueled telecom buildout of the late 1990s played a similar role in the 2001 recession.

Notice the common thread – debt. It turns a sector’s problem into everyone’s problem.

“Three booms wearing the same trench coat”

So, which flavor of “bust” might AI bring?

Answering that one is difficult. As Tom explains:

AI isn’t a single boom. Instead, it’s all three booms wearing the same trench coat.

At the top are cash-rich mega-caps that still fund most of their AI spending from operating cash flow. They look a lot like Apple in the 2010s.

In the middle are companies in crowded, competitive niches spending other people’s money: frontier AI labs, AI chip startups, and humanoid robot makers. Tom notes that, like the early automakers, not all of them can survive.

At the bottom are companies like CoreWeave, built almost entirely on borrowed money. Here’s Tom:

These are the most dangerous types of AI bets because they’re relying on enormous amounts of borrowed capital to build capacity no one knows will be needed.

This framing also explains why the AI bubble debate produces such contradictory answers from smart people. Each side is usually describing a different part of the trench coat.

Tom’s base case, and the signposts that would change it

For now, Tom believes we’re set up for the mildest version:

If the AI trade were to sour today, we think the selloff would most closely resemble the “platform bust” of the smartphone revolution.

The most speculative companies would take the damage, while the broader economy escaped largely unscathed.

His reasoning is that today’s market is anchored by the Magnificent Seven and other well-funded tech giants. Together, they account for nearly half of the S&P 500, creating a cash-rich buffer.

Of course, the “mild” version could be anything but mild for many AI stocks. As we highlighted in yesterday’s Digest, Eric’s view is that some AI Builders could fall 50% or more. Today alone, I’m looking at many AI Builders down double digits. 

Tom believes the more speculative trades could lose everything:

We will likely see dozens of frontier AI labs and advanced robotics firms shutter, and perhaps some highly leveraged “neocloud” companies as well.

But what might cause the damage to spread – changing a platform bust into something worse?

Tom flags two signposts. The first is the speculative middle tier going public:

Every IPO like this moves more of the eventual losses from venture funds to ordinary shareholders, which is how the PC and solar booms turned into industry-wide busts.

That’s already underway…

SpaceX (SPCX) went public in June in a record IPO. OpenAI has confidentially filed for its own. And Anthropic is reportedly targeting a listing as soon as mid-November at a potential valuation near $2 trillion, which would rank among the largest IPOs ever.

If this trend continues, Tom says it would be wise to trim exposure across the whole AI sector.

The second signpost – in this case, pointing toward an “economy-wide bust” – is the big one: the Mag 7 being forced to borrow to keep the buildout going.

To be clear, big, profitable companies borrow all the time, often simply because debt is cheap. Tom’s warning is about the moment borrowing stops being a choice and becomes a necessity, when AI spending outruns the cash these companies generate.

This isn’t as far-fetched as you might think. A Goldman Sachs analysis projects that annual spending on AI infrastructure will reach $1.6 trillion by 2031. By Tom’s math, that’s six times the cash the Mag 7 companies currently hold.

Here’s Tom on where that could lead:

If this keeps going for long enough, even the best Mag 7 firms will end up looking like fiber optic firms in the 1990s.

They will be forced to borrow enormous sums of cash, creating that perfect environment for a new credit crisis.

Coming full circle

Which brings us back to Meta.

Last night, the hyperscaler stepped into the early stage of Tom’s second signpost. Its capex now exceeds the cash its business generates. It holds more debt than cash. And it just created a new class of stock it can sell to raise money.

One company’s cash-burning quarter isn’t a credit crisis. But it’s the direction worth watching as the rest of the Mag 7 report in the coming days.

But for the moment, Tom’s bottom line is reassuring for the broader market, if not for your AI stocks:

For now, the stage is set for a comparatively mild AI “platform bust,” and that’s the scenario your portfolio should be built for.

Building for that scenario means avoiding the leveraged Builders at the bottom of Tom’s trench coat and owning the businesses positioned to benefit from cheaper AI. That’s the heart of Eric’s Separation thesis that we covered in yesterday’s Digest.

For help on what this means in practice, Eric’s Apogee system recently flagged four AI Appliers: overlooked companies that are using increasingly cheap AI to improve their businesses.

And in his new presentation, Eric reveals his No. 1 pick to buy ahead of November 4, the day after the midterms, when he expects the Separation to accelerate. He’s sharing the name and ticker for free, with no signup required.

Click here to watch Eric’s presentation and get the free name.

We’ll keep watching these signposts, and what they tell us about which kind of bust could be headed our way – or already here.

Have a good evening,

Jeff Remsburg

(Disclosure: I own HD, AAPL)

The post Could an AI Bust Crash the Whole Market? appeared first on InvestorPlace.

You see, Eric and I don’t always agree on everything. But I know he has an impressive track record of identifying opportunities that the rest of Wall Street overlooks. He’s made some remarkable calls over the years, including during the dot-com boom.

And he’s made his followers a lot of money in the process.

Now, he believes another major shift is taking shape in the AI Revolution.

In fact, Eric is warning that some of today’s biggest AI stocks could plunge 50% or more as early as November 4. But he’s also identified a handful of overlooked companies that could emerge as the next big winners.

Better yet, he’s revealing his No. 1 stock recommendation, including the ticker symbol, absolutely free.

That’s why I urge you to watch Eric’s latest special presentation right now. You’ll discover why he believes a major shakeup is coming to the AI market – and how you can position yourself to potentially profit from it before November 4.

But first, Eric has a fascinating story from more than 130 years ago that helps explain what he sees coming…

*************************

Hello, Reader.

In February 1893, America’s railroad empire began to collapse.

Railroad companies that had spent a fortune building the infrastructure found themselves drowning in debt.

The Philadelphia and Reading Railroad collapsed under the weight of its debts in February. Others soon followed. Between 1892 and 1897, railways operating roughly 60,000 miles of track passed into receivership. It was a period of financial distress that hit about one-third of the national network.

Investors lost fortunes, and the failures helped fuel the Panic of 1893, a financial crisis that sent stocks tumbling, banks failing, and the economy into a severe depression. Industrial production fell more than 15% between 1892 and 1894.

Meanwhile, other businessmen were making a fortune on the same railroad tracks.

In 1903, Ladies’ Home Journal became the first American magazine to reach 1 million in circulation.

Its publisher, Cyrus H.K. Curtis, was delivering magazines to households from New York to California. And he managed this remarkable feat without laying a single railroad tie, purchasing a locomotive, or borrowing millions of dollars to build a railroad.

While his publishing empire was growing through the railroad infrastructure, the railroad industry that made it possible was suffering one of the worst financial crises in its history.

That’s one of the great, underappreciated lessons of investing in a technological revolution: The companies that build the infrastructure aren’t usually the ones that make the most money from it.

Sometimes, the biggest winners are the businesses that put that infrastructure to work.

Today, I’ll explain why the railroads went broke, how similar financial pressures are threatening today’s AI giants, and where investors might find the next generation of winners.

I’ll also give you a healthcare stock recommendation that I believe is already benefiting from AI.

How the Railroad Boom Went Off the Rails

Railroad mileage exploded during the 1880s. Investors poured money into new lines, convinced that whoever controlled the tracks would control the movement of goods and collect the profits.

But building railroads was enormously expensive. Companies had to acquire land, lay track, build bridges, and buy locomotives, often with borrowed money. Those debts still had to be repaid whether the trains were full or half-empty.

Meanwhile, the technology kept improving. Steel rails replaced iron ones, allowing trains to carry heavier loads. Westinghouse air brakes made longer trains safer. Better signaling systems let railroads move more traffic over existing tracks.

These innovations were wonderful for the American economy. But they also increased transportation capacity and intensified competition, putting pressure on freight rates.

The railroad companies had borrowed fortunes to build their networks. Then technological improvements helped make the services those networks provided cheaper and cheaper.

That’s a fine arrangement for anyone shipping freight. It’s a considerably less attractive arrangement for the folks trying to pay off the locomotives.

Many railroad companies couldn’t survive. The railroads themselves, however, remained indispensable.

Curtis Publishing was among the businesses that benefited. It could use the rail network to reach customers nationwide without financing the network itself.

The railroad builders spent the money. Curtis got to use what they’d built.

And I’ve seen this pattern before.

In December 2000, I warned investors away from Corning Inc. (GLW), a major supplier of the fiber-optic cable being laid to build the internet. Barron’s picked up my warning, and Corning subsequently plunged 87%.

That same month, I recommended an altogether different kind of Internet investment:

Humana Inc. (HUM). Humana wasn’t laying fiber-optic cable. It was using the internet to make its existing health insurance business more efficient, moving claims and records online and reducing costs. While the internet’s infrastructure builders struggled, Humana eventually gained more than 4,000% following my recommendation.

Corning helped build the internet. Humana found ways to use it. One stock collapsed 87%. The other eventually gained more than 4,000%.

The internet worked beautifully. That didn’t mean every internet investment would.

And now I believe we’re seeing a similar divide emerge in artificial intelligence.

Wall Street May Be Making the Same Bet Again

Microsoft Corp. (MSFT), Amazon.com Inc. (AMZN), Alphabet Inc. (GOOGL), Meta Platforms Inc. (META), and other technology giants are spending hundreds of billions of dollars building AI infrastructure.

Amazon alone is planning roughly $220 billion in capital expenditures this year, much of it tied to AI infrastructure and the computing capacity needed to support it.

There’s a good reason for all this spending. AI is transforming businesses, and demand for computing power remains enormous.

But these companies are making a very expensive bet about what that demand will look like years from now. And I believe they’re beginning to face the same two financial pressures that squeezed the railroads.

First, building infrastructure keeps getting more expensive. Data centers require enormous amounts of electricity, water, land, and equipment. Communities are pushing back against new projects, particularly when residents worry about higher utility bills.

According to real estate firm Cushman & Wakefield, data-center construction costs have risen 21% per megawatt since late 2024.

Second, the technology itself keeps getting cheaper and more efficient. In January 2025, China’s DeepSeek demonstrated that advanced AI models could operate much more efficiently than many investors had assumed. Meanwhile, AI developers are finding ways to deliver more computing power for less money. New models, chips, and software are steadily improving what each dollar of AI spending can accomplish.

Cheaper computing is wonderful for businesses that want to use AI. But it could become a problem for companies that have spent billions building infrastructure on the assumption that computing power will remain scarce and expensive.

What happens if tomorrow’s chips can do substantially more work than today’s? Or if new software dramatically reduces the computing power needed for a task?

The data centers don’t become useless. But their owners may struggle to earn the returns they expected.

Now, there’s an obvious objection to this argument: Cheaper AI could encourage so much additional use that demand for computing power continues to soar. In fact, history offers plenty of examples of falling costs producing explosive growth in demand.

But explosive demand doesn’t guarantee explosive profits. Especially when the companies chasing that demand must continually spend billions to keep up.

And that’s why I’m increasingly interested in companies on the other side of this equation.

The Next Cyrus Curtis May Be in Healthcare

Developing a new drug is notoriously expensive and uncertain. Researchers can spend years identifying promising biological targets, testing thousands of molecules, and deciding which candidates deserve further development.

AI could accelerate that work dramatically. It can already analyze genetic and clinical data, identify drug targets, and guide experiments before scientists enter the laboratory.

And pharmaceutical companies don’t need to become AI infrastructure providers to benefit. They simply need to put the technology to work.

One example is Bristol-Myers Squibb Co. (BMY).

I’ve recommended BMY to my members since February 2024, when I first advised readers to buy shares at $56 or below. It hasn’t exactly been a Wall Street favorite. Investors have worried about the company’s earnings outlook and future drug pipeline.

But Bristol Myers is investing heavily in AI-assisted drug discovery. In July, it announced plans to become the first life-sciences company to purchase a supercomputer powered by Nvidia Corp.’s (NVDA) latest Vera Rubin technology. The company intends to use that computing power to design medicines, identify drug targets, and guide experiments before laboratory work begins.

Here’s the distinction. Bristol Myers may be buying sophisticated AI equipment. But its business isn’t selling computing power. Its business is developing and selling medicines.

I call companies like this AI Appliers.

If AI helps Bristol Myers discover promising drugs faster, reduce failed experiments, and improve research productivity, those benefits could eventually show up in its earnings.

Meanwhile, the stock remains relatively inexpensive. In late September, BMY traded at less than 12 times forward earnings. I continue to recommend BMY to my members up to $70 per share.

Of course, AI won’t magically transform every experimental drug into a blockbuster. Drug development remains an expensive, failure-prone business, and Bristol Myers still faces challenges in its existing portfolio.

But that’s precisely why the stock interests me. Wall Street isn’t pricing BMY as an AI superstar. It’s pricing the company as a pharmaceutical business with problems to solve. If AI helps solve even a few of them, investors could be pleasantly surprised.

And BMY is hardly alone. Across healthcare, manufacturing, energy, and other industries, companies are discovering ways to use AI to improve their businesses. Many of the most promising are still being overlooked by Wall Street.

That’s where I’m spending more and more of my research time.

Who Gets Rich After the Boom

The railroad bust of 1893 didn’t end the railroad age. Nor did the dot-com crash end the internet revolution.

In both cases, the technology survived. And investors who understood how businesses could profit from it found extraordinary opportunities.

I expect AI to follow a similar path.

Some of today’s AI infrastructure giants may become spectacular long-term investments. Others may discover that building the future is a very expensive way to make a disappointing return.

Meanwhile, thousands of companies will have the opportunity to use that infrastructure without paying to build it. That’s the part of the AI Revolution that interests me most.

Bristol Myers is one example. I’ve identified several others that I believe offer even greater upside potential.

In fact, I’ve just recorded a free special presentation explaining why I believe November 4 could mark the beginning of a major shift in the AI market — and which companies I expect to benefit.

During the presentation, I reveal my No. 1 AI Applier, including its name and ticker symbol. You don’t need to buy anything to get that recommendation. Click here to watch my new presentation and get my No. 1 AI stock pick for free.

Cyrus Curtis didn’t need to own a railroad to build a publishing empire. He just needed the trains to run.

Regards,

Eric Fry

Senior Global Macro Analyst, InvestorPlace

The post What a 19th-Century Magazine Can Teach Us About AI Stocks appeared first on InvestorPlace.

The post How to Build a Crisis-Proof, Inflation-Proof Portfolio appeared first on InvestorPlace.

In October 2003, the Brian Jonestown Massacre released a song called “A New Low in Getting High.”

The California retro-rock band wasn’t singing about the stock market, of course. But it might as well have been writing the dot-com bubble’s epitaph.

In the months leading up to March 2000, when the Nasdaq Composite reached its dot-com peak, the index kept setting records… even as fewer and fewer stocks participated in the rally.

By the time the Nasdaq hit its high, plenty of stocks were already having a miserable time. Then the bubble burst.

Over the next two and a half years, the Nasdaq Composite plunged 78% from that peak, finally hitting bottom in October 2002.

And now we may be seeing something disturbingly similar.

I like to compare the stock market to a cocktail party. A healthy party has people mingling, laughing, and generally enjoying themselves. The more guests participating, the better the party.

But when a handful of guests are laughing in the corner while most of the room is plotting an escape, the festivities have taken an unpleasant turn.

Lately, that’s been the stock market.

Over the past 18 months, the Nasdaq-100 has closed at record highs 55 times. But during its three most recent record-setting days, an average of just 764 stocks across U.S. exchanges reached new 52-week highs.

A year earlier, that figure was 1,581.

The Nasdaq-100 keeps setting records, but fewer and fewer stocks are joining the celebration … a stat eerily close to the market before the dot-com bubble burst.

It’s worth asking what investors can do about it. After all, knowing that a party is going badly isn’t especially useful unless you know where the exits are, or where else you might want to spend the evening.

Today, I’ll show you why this market deserves caution — and give you the name of an overlooked healthcare stock that I believe offers substantial upside, even if the market’s party keeps shrinking.

The Music’s Still Playing, but Look at the Room

Take a look at the chart below.

The green line shows the Nasdaq-100, which has been marching steadily higher. Nothing terribly alarming there.

But the black line tells a very different story. It measures the number of stocks across U.S. exchanges hitting new 52-week highs, minus those falling to new 52-week lows, averaged over two weeks. When that line drops below zero, more stocks are hitting new lows than new highs.

And lately, it’s fallen off a cliff.

The Nasdaq-100 is setting records while hundreds more stocks are hitting new lows than new highs. That’s an unhealthy combination.

During the Nasdaq Composite’s final 34 record-high days before the dot-com crash, new lows outnumbered new highs on the New York Stock Exchange on 31 of those days.

I’m not suggesting we’re about to experience another 78% collapse. History rarely repeats itself quite so obligingly.

But I’ve been around long enough to know that when the market’s leaders keep climbing while the rest of the market deteriorates, trouble can follow.

One reason for this growing imbalance is what I call a self-fulfilling buying cycle. The market’s biggest companies attract an enormous amount of investment money. As their stocks rise, index funds and professional investors buy more of them. That additional buying pushes prices higher, which attracts still more money.

Meanwhile, smaller companies and less fashionable industries get left behind.

The popular stocks become more popular because they’re going up. The unpopular stocks become less popular because they aren’t. It’s a remarkably simple process, and one that can continue much longer than common sense might suggest.

Eventually, that concentration makes the entire market more vulnerable. If the handful of companies doing the heavy lifting stumble, there aren’t many others ready to pick up the slack.

My advice is simple: Don’t confuse a market hitting record highs with a market that’s getting stronger. And don’t assume the stocks everybody wants to own are necessarily the best investments available.

In fact, some of the most interesting opportunities may be hiding among the stocks Wall Street has stopped inviting to the party.

Which brings me to a company that’s about as far removed from Silicon Valley’s AI frenzy as you can get.

A Healthcare Giant Wall Street Has Left Off the Guest List

Novo Nordisk A/S (NVO), the Danish pharmaceutical giant behind Ozempic and Wegovy, used to be one of Wall Street’s favorite stocks.

Then its longtime rival, Eli Lilly & Co. (LLY), began winning the battle for the lucrative obesity-drug market. Lilly’s Zepbound delivered better weight-loss results than Novo’s injectable Wegovy in a landmark clinical trial, and investors responded accordingly.

Over the past five years, Lilly’s stock has gained roughly 400%, while Novo’s has lost ground.

Wall Street seems to have decided that Lilly has won the obesity-drug race, collected the trophy, and retired the competition. I think the victory celebration may be premature.

Novo currently trades at roughly 14 times earnings, compared with 34 times for Lilly. Its market capitalization is about one-fifth of Lilly’s, even though their obesity and diabetes businesses generate similar annual sales.

That’s a remarkable valuation gap between two companies competing in the same enormous market.

And here’s what Wall Street may be missing: Lilly may have won the battle of the injections, but Novo has taken an early lead in pills.

In January, Novo launched the first oral GLP-1 treatment for obesity, the Wegovy pill. During its first six months, it racked up approximately 5 million prescriptions, capturing roughly 76% of the U.S. oral obesity-drug market.

Lilly’s competing pill arrived in April but has yet to match that momentum.

The appeal of an effective obesity pill is obvious. Millions of patients would prefer swallowing a tablet to injecting themselves every week. And whichever company captures a meaningful share of that market could enjoy a very profitable future.

Novo also has a promising pipeline of new treatments, including its next-generation obesity drug CagriSema, along with therapies targeting blood disorders and liver disease.

And it’s putting AI to work through partnerships with Microsoft Corp. (MSFT), OpenAI, Amazon.com Inc. (AMZN), and other technology companies to accelerate drug discovery and improve its operations.

That’s what I call an AI Applier: an established business using AI to improve its profitability rather than spending billions building the infrastructure behind it.

Novo doesn’t need to invent the next generation of AI models. It simply needs to use them to develop better medicines, more efficiently.

Of course, Novo isn’t without risks. Lilly remains a formidable competitor, and Novo faces pricing pressure, patent expirations, and uncertain regulatory outcomes.

And cheap stocks have a habit of remaining cheap when the underlying business fails to improve. That’s why I never consider a low valuation, by itself, a compelling reason to buy.

But Novo is still a highly profitable pharmaceutical company with established products, a substantial research pipeline, and a potentially valuable head start in oral obesity treatments. Those are meaningful assets, even if Wall Street has temporarily lost its enthusiasm for them.

At the beginning of this year, I called Novo one of my “Top 7 Stocks for 2026.” At today’s prices, I believe Novo could potentially double and still trade at a discount to Lilly’s valuation. That outcome isn’t guaranteed, of course. But it illustrates just how much pessimism investors have already baked into Novo’s share price.

In a new special report, I explain a strategy that could produce even larger percentage gains if my forecast for Novo proves correct. It also involves greater risk than simply owning the shares. That report is one of the bonuses available to investors who take action after watching my new free presentation.

And Novo is just one of the opportunities I’ve been researching.

I believe an even bigger investment shift could begin around November 4, as the market starts distinguishing between companies spending enormous sums building AI infrastructure and those putting AI to profitable use.

I’ve recorded a free special presentation explaining what I’m seeing. During it, I’ll reveal the name and ticker of my No. 1 AI Applier, another company I believe is positioned to benefit from this shift.

Click here to watch my free presentation and discover my No. 1 AI Applier stock pick.

As for the stock market’s cocktail party, I’m not suggesting you leave just because a few guests have become obnoxiously loud.

But when most of the room is heading for the exits, it pays to notice.

And while the crowd continues to celebrate the same handful of fashionable stocks, I’ll keep looking for opportunities in the quieter corners of the market.

Regards,

Eric Fry

Senior Global Macro Analyst, InvestorPlace

The post As the Market’s Party Shrinks, Here’s One Stock to Buy appeared first on InvestorPlace.

Earlier this week, something remarkable happened on a Ukrainian battlefield.

A wounded soldier was stranded in a minefield as enemy drones circled overhead. Traditional rescue vehicles could not reach him, so Ukrainian forces tried something extraordinary.

They sent in a drone.

A massive six-rotor drone originally designed to drop bombs.

The soldier strapped himself to the aircraft, which lifted him off the battlefield, carried him over dangerous terrain, and lowered him to safety.

The Ukrainian military described the mission as the world’s first aerial drone evacuation of a wounded soldier.

Think about that for a second.

Technology that once existed primarily in science fiction is now saving lives on the battlefield. And that transformation is happening everywhere.

Artificial intelligence is accelerating drug discovery, redesigning computer chips, automating factories, and changing how companies operate.

The technology is real, and so are the investment opportunities.

But just because a technological revolution is real does not mean every stock riding that revolution is a great investment. We learned that lesson during the internet boom of the late 1990s.

The internet changed the world, just as investors expected. But plenty of internet stocks collapsed anyway. And today, with AI stocks commanding enormous valuations, borrowing costs rising, and market leadership narrowing, investors are confronting a familiar question:

Is AI another bubble?

I was asked that question on the new The InvestorPlace podcast and here’s what I said:

“Of course AI is a bubble.”

But the real question could determine whether investors make fortunes or lose them is much more important:

When does the bubble pop?

And in the latest episode of The InvestorPlace, my colleagues Louis Navellier, Eric Fry, and Jonathan Rose tackle that question from three very different perspectives.

Their discussion reveals why this market is becoming increasingly dangerous, and why I believe the AI boom still has room to run. Give it a watch here:

Why I Am Still Bullish on AI Stocks

So, yes, I believe we are in an AI bubble.

I also believe that bubble has not reached its breaking point.

Why? Because the money is still flowing.

Companies are still expanding AI infrastructure. Semiconductor demand remains strong. And the recent pullback in major chip stocks has brought buyers back around important technical support levels.

Louis Navellier pointed to Nvidia Corp. (NVDA) and Micron Technology Inc. (MU) as compelling opportunities during the sell-off. He also highlighted Bloom Energy Corp. (BE) because AI data centers need reliable electricity.

Those are precisely the kinds of businesses benefiting from the infrastructure demands of this revolution.

Still, Eric Fry raised an important counterargument.

Even excellent businesses can become poor investments when expectations grow too high.

That is why he favors finding opportunities beyond the most crowded AI trades, including companies applying AI in pharmaceuticals and medical technology.

It is a perspective worth considering.

The AI Boom Is Entering a New Phase

The late 1990s created enormous wealth before the dot-com bubble burst. I believe the late 2020s could offer investors a similar opportunity. But there’s a catch…

The stocks that made investors rich during the first phase of the AI Revolution may not be the same stocks that lead its next phase.

And that is precisely what my colleague Eric Fry is warning about.

Eric believes two powerful forces are converging on America’s biggest AI companies: increasingly expensive financing and growing political opposition to the massive data centers powering this revolution.

Consider what happens over the next two weeks.

Meta Platforms Inc. (META) just reported earnings last night; Microsoft Corp. (MSFT) follows on Oct. 28, with Alphabet Inc. (GOOGL) and Amazon.com Inc. (AMZN) expected to report around the same time.

Investors will be watching their AI spending plans closely.

Then, on Nov. 3, Americans head to the polls for the midterm elections.

And data centers have become a surprisingly contentious political issue, with politicians from both parties calling for restrictions and demanding that technology companies shoulder more of the costs of their enormous electricity needs.

That creates an interesting possibility.

While the companies building AI infrastructure face higher costs and mounting political pressure, companies applying AI to improve their businesses could emerge as the next market leaders.

Eric calls this potential shift “the Separation.”

And he believes it could begin as soon as Nov. 4.

Now, I remain bullish on the long-term AI Revolution. But Eric makes a compelling case that investors need to start looking beyond the companies that have dominated the trade so far.

In fact, he has identified a group of overlooked AI stocks he believes could benefit as capital rotates away from the market’s biggest names.

He is even revealing his No. 1 AI Applier stock pick for free.

Watch Eric Fry’s special briefing here to discover why he believes the AI boom could split in two after the midterm elections — and which overlooked stock he recommends buying before that happens.

Because the next fortune in AI may just come from the companies putting that revolution to work.

The post Is the AI Bubble About to Pop? Where 4 Experts Are Putting Money appeared first on InvestorPlace.

Last week, Elon Musk summed up the AI trade’s latest scare in a single word…

He was reacting to CoreWeave Inc. (CRWV), the “neocloud” that rents out banks of Nvidia (NVDA) chips to AI companies.

Within days, some of CoreWeave’s bonds traded below 80 cents on the dollar, and the yield on its 2031 notes briefly topped 16%. That’s distressed-debt territory.

The stock lost about a quarter of its value on the week as panicked investors fled.

So, what sparked the fear?

CoreWeave is funding its growth the way much of the AI buildout now is – with borrowed money. It’s carrying roughly $52 billion in loans and lease obligations.

Analysts expect CoreWeave to generate about $13 billion in revenue this year, against planned capital spending of $35 billion to $39 billion and a projected loss of more than $2 billion.

This isn’t great math for investors. And many on Wall Street fear that the company won’t earn enough on all that spending to service its debt.

Last Wednesday’s hot inflation report made it worse by raising the odds of another Fed rate hike – which means pricier borrowing ahead. By Thursday, the cost of insuring CoreWeave’s debt against default had hit a record. Protecting $1 million of its bonds would cost roughly $119,500 a year.

Stepping back, when lenders treat a prominent AI player like a credit risk, that gets our attention – and Luke Lango’s.

Here’s Luke, our technology expert and the editor of Innovation Investor:

Bond markets tend to sniff out trouble before stock markets do.

So, if the bond market is right, what comes next for the AI boom? And more importantly, how should you be positioned?

How late in the AI boom are we?

Last week in his Innovation Investor service, Luke introduced a tool designed to answer that question. Here he is explaining his rationale:

We’re staying bullish, but we’re not blind.

Every great boom ends. The railroads did, the dot-coms did, and someday the AI buildout will too.

The problem is that nobody rings a bell at the top.

It’s called the Peak Watch Checklist. It tracks 13 warning signals across three stages a boom moves through on its way down: Froth, Cracks, and Confirmation. Each signal comes with a specific “tripwire” that would flip it to red.

So, where are we?

Luke says the Froth stage is fully red. Big Tech is borrowing to fund AI spending, suppliers are financing their own customers, and stock issuance is setting records. And in Monday’s Daily Notes, the reading moved in the wrong direction.

Here’s Luke:

Our Peak Watch Checklist now has 7 of 13 signals lit, up from six last week.

Credit concerns have spread beyond CoreWeave, while TSMC’s selloff after strong results pushed “good news gets sold” into Flashing territory.

Most signals that would confirm a bust remain clear. We’re still in a late-cycle boom, where some of the biggest gains can happen.

As Luke clarified at the end, he isn’t yet calling a top…

Chips are still selling out, and North American data-center vacancy sits at just 1.4%. Luke’s own long-term math even gives a 60% probability that AI revenue ultimately justifies the spending – though his base case doesn’t see full payback until around 2039. That’s a long runway for financing scares that can rattle your portfolio.

So, perhaps the better question to ask isn’t “when?” but rather, “who?”

Specifically, when the boom turns, who gets hurt – and who survives?

Back to Luke:

We favor companies with pricing power, strong cash flow, and productive uses for AI.

Businesses borrowing heavily to build capacity for others face greater risk.

If revenue disappoints, spending will fall, and the damage will land hardest on those that overbuilt.

That last line is the bridge to today’s most important idea. It comes from our global macro expert Eric Fry, editor of The Speculator – who thinks we could be watching history repeat itself.

Corning built the internet – but Humana used it

Rewind to December 2000.

The dot-com bubble had begun to deflate, but investors still loved the companies building the internet’s plumbing. Corning (GLW), which made the fiber-optic cable carrying all that traffic, was a market darling.

That month, Eric warned investors away from Corning. Its stock went on to fall 87%.

That same month, he recommended Humana (HUM), a beaten-down health insurer that was quietly using the internet to make its business more efficient. Humana eventually gained more than 4,000%.

The difference between the two companies – and their ensuing returns – was simple…

Corning was helping build out the internet. Humana was putting it to work.

Eric believes the AI boom is about to split along the same line. He calls it “The Separation.”

On one side are the AI Builders – companies like Microsoft (MSFT), Meta (META), and Micron (MU) that are spending (or supplying) enormous sums on AI infrastructure. Eric believes some of these stocks could fall 50% or more.

On the other side are the AI Appliers – overlooked companies using increasingly cheap AI computing power to improve their businesses. Some of them aren’t even classified as tech stocks.

Now, it’s important to treat this carefully: Eric isn’t calling for a broad crash – he’s pointing toward a massive market sorting.

The vise closing on the Builders

Eric sees two forces squeezing the Builders like the jaws of a vise.

The first is the Revenue Jaw: computing power keeps getting cheaper as AI models and chips become more efficient. That’s great for AI users, but it threatens the economics of infrastructure built at yesterday’s prices.

It’s what happened to railroads in the 1880s and fiber in the early 2000s – new technology multiplied the capacity of existing networks, prices fell, and many of the companies that borrowed to build them went bust.

Luke’s checklist is already tracking this.

The price of AI tokens – the units AI models charge by – hit a record low in September, down more than half from its summer peak. But GPU rental prices are still rising, so the pressure hasn’t hit the infrastructure owners yet.

Luke’s tripwire is a sustained drop in those rents. That’s the moment the Revenue Jaw reaches the Builders.

The second is the Expense Jaw: data centers are getting more expensive to build. Communities and politicians in both parties are pushing back on new projects, tax breaks, and rising electricity bills.

In September, the House voted 417-3 for a bill pushing data centers to pay the full cost of the power upgrades they require. At least 20 candidates in this year’s governor’s races have promised some form of data-center moratorium. And Gallup found that 71% of Americans oppose a data center in their community.

Meanwhile, don’t forget where we stand with interest rates and the cost of money. September’s inflation came in hot at 3.7%, and futures traders see roughly 90% odds of a December rate hike.

Expensive money will hit the borrowers first – which is CoreWeave’s story in a nutshell.

Money is moving, not leaving

Eric points to an early example of how the Separation could play out by calling back to the “DeepSeek” scare.

On Jan. 27, 2025, Nvidia lost $589 billion in market value after China’s DeepSeek demonstrated what could be done with cheaper AI technology. Yet – that very same day – the Dow finished higher.

Money didn’t leave the market. It just moved.

Something similar has been happening recently…

The iShares Semiconductor ETF (SOXX) just fell more than 16% in two weeks, leaving it 25% below its June peak – firmly in bear-market territory.

And yet, last week, while the tech-heavy Invesco QQQ Trust (QQQ) suffered its worst week in more than a year, the Consumer Staples Select Sector SPDR ETF (XLP) rose 5% for its best week since February, while the Energy Select Sector SPDR ETF (XLE) climbed more than 4%.

That isn’t proof the Separation has begun – but it’s certainly what a beginning might look like.

Will the next two weeks bring fireworks?

The next two weeks will tell us a great deal more about whether this is playing out…

Meta reports earnings tonight after the close. The Fed meets next Tuesday and Wednesday. Microsoft and Alphabet (GOOGL) report next Wednesday, with Amazon (AMZN) expected on Thursday. Then come the midterm elections on November 3.

Basically, we have wave after wave of potential market-moving events.

Here’s Luke with what he’s watching for in the earnings reports:

The key is whether financing stress starts changing business decisions: fewer chip orders, more canceled projects, or cuts to capex.

As for Eric, he’s circled the day after all of it: November 4, the morning after the midterms.

That’s when he believes the Separation will accelerate – regardless of which party wins. With data-center backlash coming from both sides of the aisle, he believes the pressure on the Builders intensifies either way – which is why he’s getting into position now.

How to get on the right side of the Separation

Eric has been using his Apogee system – which scans roughly 14,000 stocks against nine factors – to find neglected companies whose businesses are improving.

Among his tests: the shares have fallen at least 40% from their highs, sales are growing, and the stock is cheap relative to those sales.

After his latest scan, four AI Appliers passed. And in a new presentation, Eric is revealing his No. 1 pick to buy ahead of November 4 – name and ticker included – for free.

There’s no sign-up required to access Eric’s research. Just click here to watch his presentation now – and get the free name.

Coming full circle

Luke’s checklist tells us how late in the AI boom we are. Eric’s framework tells us where to be invested when it turns.

While their market views diverge in some places, they both agree on the bigger picture: AI isn’t going away, but its rewards won’t be shared equally. Over the next two weeks, the goal is to make sure you’re on the right side of that divide.

Have a good evening,

Jeff Remsburg

(Disclosure: I own GLW, MSFT, MU)

The post The AI Trade Is About to Split in Two appeared first on InvestorPlace.

Those are the decisions behind the AI bubble question in this week’s episode of The Investor Place. Host Crystal Navellier sits down with Louis Navellier, Eric Fry and Jonathan Rose, with Luke Lango adding his perspective in a recorded segment.

The conversation brings together four investing approaches to examine the same market: the earnings behind the rally, the risks beneath the headlines and the opportunities investors may want to consider next.

Click the image below to watch the full episode on YouTube.

What Should Investors Look for in an AI Bubble?

A company’s growth, its stock price and the health of the broader market are different pieces of the investment picture. The episode examines how they fit together — and what investors might miss by focusing on just one.

Louis and Eric draw on their experience investing through the dot-com era to explore how useful that comparison is today. Jonathan brings the discussion to the financing behind AI’s expansion, while Luke’s recorded commentary turns attention to the question of timing.

Along the way, they consider several questions that can shape an investment decision:

• How much good news is already reflected in AI stock prices?
• What can smaller stocks reveal about a market led by large technology companies?
• What would signal a meaningful change in the outlook?

Where to Invest as the AI Story Develops

The discussion also gets specific about the stocks and sectors on the experts’ radar. They consider how to evaluate a pullback, where to look for opportunity and how to think about exposure when the market feels uncertain.

For investors deciding what to do with new money — or with gains already on the table — the value is in hearing how these analysts reach their conclusions. Which evidence carries the most weight? What would make them reconsider?

Watch the full conversation for their answers, the investments they discuss and the signals they’re watching next.

Watch This Week’s Episode — and Subscribe

The Investor Place podcast brings you weekly conversations about what’s moving markets, what it means for your money and where the next opportunities could be.

Subscribe to InvestorPlace on YouTube to follow the conversation each week.

Find more episodes on the InvestorPlace YouTube channel.

Catch up on last week’s episode: Where to Invest $10,000: 3 Experts Share Their Next Moves.

Learn More About This Episode’s Experts

Get to know Louis Navellier, Eric Fry, Jonathan Rose and Luke Lango — and explore their investing strategies, free content and premium research services.

Louis Navellier: Meet the down-to-earth investor behind the candid market commentary—and explore the stock-picking strategies he’s honed over more than four decades.

FREE SIGN UP: Get Louis’s Market360 e-letter.

Eric Fry: From AI to commodities, uncover the global shifts—and overlooked companies—at the heart of his search for the next big investment opportunity.

FREE SIGN UP: Get Eric’s Smart Money e-letter.

Jonathan Rose: See how a former options market maker tracks unusual options activity and pricing gaps to turn market signals into trade ideas.

FREE SIGN UP: Join Jonathan’s Masters in Trading class.

Luke Lango: See how a Caltech-trained analyst combines data modeling and startup experience in his search for breakthrough technology investments.

FREE SIGN UP: Get Luke’s Hypergrowth Investing e-letter.

The post Are We in an AI Bubble? 4 Investing Experts Tackle the Trillion-Dollar Question appeared first on InvestorPlace.

In February 1893, America’s railroad empire began to collapse.

Railroad companies that had spent a fortune building the infrastructure found themselves drowning in debt.

The Philadelphia and Reading Railroad collapsed under the weight of its debts in February. Others soon followed. Between 1892 and 1897, railways operating roughly 60,000 miles of track passed into receivership. It was a period of financial distress that hit about one-third of the national network.

Investors lost fortunes, and the failures helped fuel the Panic of 1893, a financial crisis that sent stocks tumbling, banks failing, and the economy into a severe depression. Industrial production fell more than 15% between 1892 and 1894.

Meanwhile, other businessmen were making a fortune on the same railroad tracks.

In 1903, Ladies’ Home Journal became the first American magazine to reach 1 million in circulation.

Its publisher, Cyrus H.K. Curtis, was delivering magazines to households from New York to California. And he managed this remarkable feat without laying a single railroad tie, purchasing a locomotive, or borrowing millions of dollars to build a railroad.

While his publishing empire was growing through the railroad infrastructure, the railroad industry that made it possible was suffering one of the worst financial crises in its history.

Curtis didn’t have to pay for the bridges, tunnels, locomotives, or thousands of miles of track that made his business possible. Other investors had already paid for all that, and many lost fortunes doing it.

That’s one of the great, underappreciated lessons of investing in a technological revolution: The companies that build the infrastructure aren’t usually the ones that make the most money from it.

Sometimes, the biggest winners are the businesses that put that infrastructure to work.

Today, I’ll explain why the railroads went broke, how similar financial pressures are threatening today’s AI giants, and where investors might find the next generation of winners.

I’ll also give you a healthcare stock recommendation that I believe is already benefiting from AI.

How the Railroad Boom Went Off the Rails

Railroad mileage exploded during the 1880s. Investors poured money into new lines, convinced that whoever controlled the tracks would control the movement of goods and collect the profits.

But building railroads was enormously expensive. Companies had to acquire land, lay track, build bridges, and buy locomotives, often with borrowed money. Those debts still had to be repaid whether the trains were full or half-empty.

Meanwhile, the technology kept improving. Steel rails replaced iron ones, allowing trains to carry heavier loads. Westinghouse air brakes made longer trains safer. Better signaling systems let railroads move more traffic over existing tracks.

These innovations were wonderful for the American economy. But they also increased transportation capacity and intensified competition, putting pressure on freight rates.

The railroad companies had borrowed fortunes to build their networks. Then technological improvements helped make the services those networks provided cheaper and cheaper.

That’s a fine arrangement for anyone shipping freight. It’s a considerably less attractive arrangement for the folks trying to pay off the locomotives.

Many railroad companies couldn’t survive. The railroads themselves, however, remained indispensable.

Curtis Publishing was among the businesses that benefited. It could use the rail network to reach customers nationwide without financing the network itself.

The railroad builders spent the money. Curtis got to use what they’d built.

And I’ve seen this pattern before.

In December 2000, I warned investors away from Corning Inc. (GLW), a major supplier of the fiber-optic cable being laid to build the internet. Barron’s picked up my warning, and Corning subsequently plunged 87%.

That same month, I recommended an altogether different kind of Internet investment:

Humana Inc. (HUM). Humana wasn’t laying fiber-optic cable. It was using the internet to make its existing health insurance business more efficient, moving claims and records online and reducing costs. While the internet’s infrastructure builders struggled, Humana eventually gained more than 4,000% following my recommendation.

Corning helped build the internet. Humana found ways to use it. One stock collapsed 87%. The other eventually gained more than 4,000%.

The internet worked beautifully. That didn’t mean every internet investment would.

And now I believe we’re seeing a similar divide emerge in artificial intelligence.

Wall Street May Be Making the Same Bet Again

Microsoft Corp. (MSFT), Amazon.com Inc. (AMZN), Alphabet Inc. (GOOGL), Meta Platforms Inc. (META), and other technology giants are spending hundreds of billions of dollars building AI infrastructure.

Amazon alone is planning roughly $220 billion in capital expenditures this year, much of it tied to AI infrastructure and the computing capacity needed to support it.

There’s a good reason for all this spending. AI is transforming businesses, and demand for computing power remains enormous.

But these companies are making a very expensive bet about what that demand will look like years from now. And I believe they’re beginning to face the same two financial pressures that squeezed the railroads.

First, building infrastructure keeps getting more expensive. Data centers require enormous amounts of electricity, water, land, and equipment. Communities are pushing back against new projects, particularly when residents worry about higher utility bills.

According to real estate firm Cushman & Wakefield, data-center construction costs have risen 21% per megawatt since late 2024.

Second, the technology itself keeps getting cheaper and more efficient. In January 2025, China’s DeepSeek demonstrated that advanced AI models could operate much more efficiently than many investors had assumed. Meanwhile, AI developers are finding ways to deliver more computing power for less money. New models, chips, and software are steadily improving what each dollar of AI spending can accomplish.

Cheaper computing is wonderful for businesses that want to use AI. But it could become a problem for companies that have spent billions building infrastructure on the assumption that computing power will remain scarce and expensive.

What happens if tomorrow’s chips can do substantially more work than today’s? Or if new software dramatically reduces the computing power needed for a task?

The data centers don’t become useless. But their owners may struggle to earn the returns they expected.

Now, there’s an obvious objection to this argument: Cheaper AI could encourage so much additional use that demand for computing power continues to soar. In fact, history offers plenty of examples of falling costs producing explosive growth in demand.

But explosive demand doesn’t guarantee explosive profits. Especially when the companies chasing that demand must continually spend billions to keep up.

And that’s why I’m increasingly interested in companies on the other side of this equation.

The Next Cyrus Curtis May Be in Healthcare

Developing a new drug is notoriously expensive and uncertain. Researchers can spend years identifying promising biological targets, testing thousands of molecules, and deciding which candidates deserve further development.

AI could accelerate that work dramatically. It can already analyze genetic and clinical data, identify drug targets, and guide experiments before scientists enter the laboratory.

And pharmaceutical companies don’t need to become AI infrastructure providers to benefit. They simply need to put the technology to work.

One example is Bristol-Myers Squibb Co. (BMY).

I’ve recommended BMY to my members since February 2024, when I first advised readers to buy shares at $56 or below. It hasn’t exactly been a Wall Street favorite. Investors have worried about the company’s earnings outlook and future drug pipeline.

But Bristol Myers is investing heavily in AI-assisted drug discovery. In July, it announced plans to become the first life-sciences company to purchase a supercomputer powered by Nvidia Corp.’s (NVDA) latest Vera Rubin technology. The company intends to use that computing power to design medicines, identify drug targets, and guide experiments before laboratory work begins.

Here’s the distinction. Bristol Myers may be buying sophisticated AI equipment. But its business isn’t selling computing power. Its business is developing and selling medicines.

I call companies like this AI Appliers.

If AI helps Bristol Myers discover promising drugs faster, reduce failed experiments, and improve research productivity, those benefits could eventually show up in its earnings.

Meanwhile, the stock remains relatively inexpensive. In late September, BMY traded at less than 12 times forward earnings. I continue to recommend BMY to my members up to $70 per share.

Of course, AI won’t magically transform every experimental drug into a blockbuster. Drug development remains an expensive, failure-prone business, and Bristol Myers still faces challenges in its existing portfolio.

But that’s precisely why the stock interests me. Wall Street isn’t pricing BMY as an AI superstar. It’s pricing the company as a pharmaceutical business with problems to solve. If AI helps solve even a few of them, investors could be pleasantly surprised.

And BMY is hardly alone. Across healthcare, manufacturing, energy, and other industries, companies are discovering ways to use AI to improve their businesses. Many of the most promising are still being overlooked by Wall Street.

That’s where I’m spending more and more of my research time.

Who Gets Rich After the Boom

The railroad bust of 1893 didn’t end the railroad age. Nor did the dot-com crash end the internet revolution.

In both cases, the technology survived. And investors who understood how businesses could profit from it found extraordinary opportunities.

I expect AI to follow a similar path.

Some of today’s AI infrastructure giants may become spectacular long-term investments. Others may discover that building the future is a very expensive way to make a disappointing return.

Meanwhile, thousands of companies will have the opportunity to use that infrastructure without paying to build it. That’s the part of the AI Revolution that interests me most.

Bristol Myers is one example. I’ve identified several others that I believe offer even greater upside potential.

In fact, I’ve just recorded a free special presentation explaining why I believe November 4 could mark the beginning of a major shift in the AI market — and which companies I expect to benefit.

During the presentation, I reveal my No. 1 AI Applier, including its name and ticker symbol. You don’t need to buy anything to get that recommendation. Click here to watch my new presentation and get my No. 1 AI stock pick for free.

Cyrus Curtis didn’t need to own a railroad to build a publishing empire. He just needed the trains to run.

Regards,

Eric Fry

Senior Global Macro Analyst, InvestorPlace

The post Stop Looking at Who Builds AI – Look at Who Puts It to Work appeared first on InvestorPlace.

One week later, on Oct. 28, Microsoft (MSFT) and Alphabet (GOOGL) do the same thing, on the same evening. Amazon (AMZN) follows roughly 24 hours after that. Apple (AAPL) closes out the parade on Nov. 2.

Then the very next morning, Americans vote in the midterm elections.

And the morning after that – Nov. 4 – is the date my colleague Eric Fry has circled in red. He believes it marks the start of the biggest shift in the AI trade since this bull market began.

Add it all up, and the next 14 days will deliver more information about the direction of the AI boom than the previous six months combined: hundreds of billions of dollars in spending plans, report cards from five of the most valuable companies on Earth, and an election in which data centers themselves are on the ballot for the first time.

Regular readers know where I stand on this buildout: I believe AI infrastructure is the defining investment opportunity of this decade, and that the companies solving its bottlenecks – power, cooling, wiring, connectivity – will keep minting winners for years to come. I’m not changing my stripes today. 

But when this much signal arrives in this short a window, the job is to stress-test what we believe. So, let’s walk through what’s coming – and why one of the sharpest investors I know thinks it ends very differently than I do.

AI Capex Is Entering a Different Kind of Earnings Season

For the past three years, AI earnings season followed a fairly simple script. A hyperscaler raises capex guidance; the market cheers. Bigger numbers meant bigger conviction, and conviction got rewarded.

That reflex is now mid-breakdown.

Organized opposition delayed or blocked an estimated $130 billion of U.S. data-center projects in the first quarter of this year alone. New York enacted the nation’s first statewide moratorium on new hyperscale facilities. More than 100 local moratoriums are under consideration nationwide. Data centers have become a campaign issue drawing opposition from both parties – and when the House voted on who should pay for the power infrastructure these facilities require, the tally was 417–3. Nothing passes 417–3 anymore. Making AI’s builders cover their own power bill does.

Meanwhile, the bond market has started grading AI paper. Debt tied to the sector’s most leveraged names repriced sharply this month, with yields on some AI-linked bonds pushing deep into double digits. Lenders have begun distinguishing between balance sheets, even when equity investors haven’t.

So, when those four CFOs step up over the next two weeks, they’re walking a tightrope that didn’t exist a year ago. Spend too little, and the market reads fading AI conviction. Spend too much, and the market may now read recklessness: more leverage, more political exposure, more capacity chasing compute prices that keep falling.

AI Infrastructure Is Getting Squeezed From Both Sides

Here’s the uncomfortable math underneath that tightrope that Eric Fry has been hammering on.

On one side, the cost of building AI infrastructure keeps rising. Politicians are shifting power costs onto developers, and the easy sites – cheap land, available grid connections, friendly neighbors – are gone. We’ve documented that force in these issues for months, from decade-long interconnection queues to a 23,000-GPU campus outside London that stalled because electricity couldn’t arrive before the 2030s.

On the other side, the price of what all that infrastructure sells keeps falling. Chips get more efficient. Models get leaner. Remember January 2025, when DeepSeek demonstrated how much AI could be done with cheaper technology and Nvidia shed $589 billion in a single session? The Dow finished higher that day. The money didn’t leave the market. It moved.

Rising costs to build. Falling prices for what you’ve built. Any business squeezed between those two forces has a problem – and the more leverage it carries, the faster the problem compounds.

On all of that, Eric and I see the same facts.

Builders vs. AI Appliers: Where Eric and I Split

Eric believes those forces trigger what he calls “The Separation“ – a split in the AI market that begins Nov. 4, no matter which party wins the midterms the night before. In his view, some of the market’s most popular AI infrastructure stocks could fall 50% or more, while investment dollars flood toward a different group entirely: overlooked companies using ever-cheaper AI to transform their businesses. The Builders stumble; the “AI Appliers” take off.

He’s made this kind of call before. In December 2000, Eric warned investors away from Corning (GLW): then one of the hottest stocks of the internet boom, laying the fiber that built the web. It subsequently fell 87%. That same month, he recommended Humana (HUM), a beaten-down health insurer quietly using the internet to run its business better. It eventually gained more than 4,000%. 

The company building the revolution cratered. The one applying it minted fortunes.

Why I Still Think AI Infrastructure Holds Up

My own view, as you likely know, is a bit different. I believe the demand side of this buildout is contractually locked in a way the dot-com era never was. 

Anthropic‘s reported $518 billion in compute commitments is roughly 80% noncancelable. OpenAI‘s revenue run rate is approaching $70 billion. And the toll collectors of this buildout are sitting on record order books: $53.4 billion at Quanta (PWR), $17.1 billion at EMCOR (EME), $15 billion at Vertiv (VRT), a record $2.4 billion at switchgear maker Powell (POWL) – which says fiscal 2027 is essentially booked – and a $4 billion cooling supply agreement at Modine (MOD) that came with a $165 million deposit paid upfront. The backbone of this buildout, in my view, keeps compounding.

Eric and I may have come to different conclusions, but we still agree on the forces, the pressure points, and the fact that the next 14 days are the test. And if this October has taught investors anything, it’s that the market has already started separating winners from losers inside this trade. 

The only open question is how far that separation runs.

The Bottom Line: Watch How the Market Reacts to AI Capex

Watch three things as the reports roll in over the next two weeks: 

• Whether capex raises get cheered or punished – the reaction-function test. 
• How the spending is funded, operating cash flow versus borrowed money, because credit markets are now grading the difference. 
• Powered capacity versus announced capacity, because as we’ve already discussed, only one is real.

By the morning of Nov. 4, we’ll know which world we’re in. Eric believes that’s the day the Separation begins. And he’s laid out his full case in a new presentation, free to watch, no signup required. 

He explains which types of companies he believes are most vulnerable, where he expects the money to flow instead, and he gives away the name and ticker of his No. 1 “AI Applier” to buy before Nov. 4.

There’s no sitting this window out. Holding through four capex reports and an election is a position, too. Go in with the full picture.

Watch Eric’s free presentation here – before the countdown runs out.

The post Meta Is About to Show Whether Bigger AI Capex Still Wins appeared first on InvestorPlace.

Eight straight sessions.

That’s how many days the Philadelphia Semiconductor Index fell before finally catching a bid yesterday.

It was the index’s longest losing streak in 18 years – you have to go back to the 2008 financial crisis to find a longer run of red for chip stocks.

And the damage wasn’t subtle…

According to Reuters, the selloff wiped out about $2 trillion in chip-sector market value during that streak. The semiconductor index lost 11.4% last week alone, its worst week since spring 2025.

Several forces combined to drive the brutal selloff. A Chinese memory maker announced advances in next-generation chips. A hot inflation report raised the odds of more Fed rate hikes. And worries grew about the mountain of debt funding the AI buildout.

But there’s an interesting twist – while the Nasdaq fell 4.5% and the S&P 500 lost about 2%, the Dow, which holds far fewer chip names, eked out a small gain for the week.

In other words, investors didn’t flee stocks. They fled AI.

Now, as I write on Tuesday near lunch, this morning’s AI bid is losing some steam. But whether the rally holds or fades, last week was a gut check for anyone whose portfolio rides too heavily on a single theme.

If that describes you, our macro investing expert Eric Fry has an idea…

Eric Fry: Familiar isn’t safe

Eric, editor of Fry’s Investment Report, recently took on an assumption most American investors never question: that U.S. stocks are simply the better place to be.

On the surface, the numbers make that case…

From the lows of 2009, the S&P 500 has delivered a total return of roughly 1,340%. That’s nearly triple the 468% return of the MSCI EAFE Index, which tracks developed markets in Europe, Australasia, and the Far East.

But Eric says the reason behind that gap isn’t what most of us would assume:

From a self-congratulatory perspective, we might assume that American technological prowess and economic dynamism have been powering the massive outperformance of U.S. stocks. But upon closer examination, we find a much more pedestrian explanation:

Multiple expansion.

We can call multiple expansion by its other name: sentiment.

So, this means that a huge chunk of the S&P’s gains came from optimistic investors simply being willing to pay higher prices for the same amount of earnings. Today, the S&P 500 trades for about 26 times earnings, compared with under 18 for the EAFE.

Now, if you rode that buying pressure higher, great. But Eric points out the flip side of that same dynamic:

Multiple expansion can’t continue forever. And when valuations stretch this far, even good news can struggle to push prices higher, while bad news can send them sharply lower.

Plus, market leadership never lasts forever.

History backs him up. Foreign developed markets have outrun the S&P 500 for long stretches before.

From 1986 to 1991, the EAFE led. In 1986 alone, it returned nearly 67%, more than triple the S&P 500’s 18.7%. It happened again from late 2003 through early 2011.

Here’s Eric’s chart tracking the back-and-forth.

Source: Fry’s Investment Report

Over the last two years, the EAFE and the S&P 500 have delivered nearly identical returns. Back to Eric for his interpretation:

This recent trend only suggests, not proves, that U.S. momentum may be fading relative to foreign stocks. Still, as we’ve seen, history shows that a shift is possible.

No matter what happens next, we American investors should never remain “overweight” in U.S. stocks and bonds, simply because they are familiar.

We must remember that, as investors, the world truly is our oyster…

Eric is already putting his money where his mouth is. In Fry’s Investment Report, he’s recommended his subscribers invest in a handful of foreign markets.

For example, in January 2025, he recommended the iShares MSCI Japan ETF (EWJ). It’s up 54% since then, easily outpacing the S&P 500’s 33% gain. Even better, Eric believes it still has plenty of runway.

EWJ isn’t the only international ETF that Eric holds in this portfolio. Plus, he has plenty of international single stocks that offer diversification from the U.S. market.

To learn about joining Eric in Fry’s Investment Report to get all his international picks, just click here.

Brian Hunt: The AI trade that runs through Brazil

What if you want to follow Eric’s advice to diversify beyond U.S. stocks but don’t want to give up your AI exposure entirely?

Back in our July 9 Digest, we highlighted senior analyst Brian Hunt, editor of the free daily newsletter Money & Megatrends, who had just offered one answer that wasn’t on the radar for many investors…

Brazil.

A couple of days earlier, Brian had made the case that the iShares MSCI Brazil ETF (EWZ) was set up to keep climbing. Part of his reasoning was AI.

Brazil is a commodity superpower, and commodities are the overlooked backbone of the global AI buildout.

Here’s Brian:

Brazil is a beneficiary of the historic AI infrastructure spending boom…

Brazil’s huge network of rivers also makes it a giant producer of hydroelectric power. This makes it an attractive destination for power-hungry AI data centers.

Brazil also has large reserves of rare earth elements. Demand for these raw materials is soaring thanks to growing demand in AI infrastructure, robotics, and defense tech.

Brian had turned bullish on Brazil all the way back in September 2025. Soon after his analysis, EWZ surged 38% in less than seven months. It then experienced a natural, healthy bull market correction from mid-April to mid-June.

But as of this past July, Brian said that correction was over, and EWZ looked poised to resume its uptrend, so he flagged it once again for his Money & Megatrends readers.

Well, congrats to Brian and his readers. Since his bullish note on July 7, EWZ has jumped another 21% while the S&P 500 is up just 2%.

Bottom line: Brazil gives you a stake in the physical side of the AI boom – the power and raw materials – without tying your portfolio to semiconductor valuations.

For more of Brian’s free analysis, he writes Money & Megatrends every day the market is open, highlighting these kinds of opportunities before they become front-page news. His issues are loaded with actionable advice and specific tickers.

You can sign up right here.

Jonathan Rose: The AI opportunity hiding halfway around the world

Brazil plays the AI boom from the natural resource side – you get AI exposure, but with some cushion from chip-stock swings. But what if you want international exposure that sits right at the heart of the AI buildout, and you’d prefer to buy it after a steep markdown?

To be clear, this isn’t a hedge against AI volatility. It’s a concentrated bet on AI memory chips – just at a discount and outside U.S. borders. But if that’s for you, there’s one place to look…

South Korea.

Last Thursday, South Korea’s KOSPI index plunged 7.6%, triggering circuit breakers and leaving the index nearly 39% below its June high.

The timing is interesting…

Just one week earlier, Samsung reported the most profitable quarter in Korean corporate history. Its preliminary third-quarter operating profit came in around 107 trillion won, or about $80 billion, up roughly 782% from a year earlier.

Record profits, collapsing stock price. That kind of disconnect is exactly what veteran trader Jonathan Rose, editor of Advanced Notice, has been watching.

Jonathan recently prepared new research for subscribers, and I’m going to pull back the curtain just a bit today, because one of the opportunities he’s eyeing is right here.

Here’s Jonathan:

I particularly like what I’m seeing in South Korea.

Most investors think about artificial intelligence in terms of familiar American companies like Nvidia Corp. (NVDA), Microsoft Corp. (MSFT), and Alphabet Inc. (GOOG).

But the AI Revolution extends well beyond Silicon Valley.

All those data centers, AI models, and increasingly sophisticated computing systems require enormous amounts of memory and semiconductor technology.

And South Korea happens to be home to two of the most important companies supplying those components: Samsung Electronics Co. Ltd. and SK Hynix Inc. (SKHY).

Both are major holdings in the iShares MSCI South Korea ETF (EWY), which gives us a way to participate in the broader South Korean stock market without selecting an individual semiconductor stock.

Jonathan recommended a trade on Korea last week – and it’s already up 22% as I write on Tuesday.

I’ll reserve the specifics for his Advanced Notice subscribers. But to get a sense of how Jonathan thinks – and generates this type of return so quickly – check out the free replay of his $10K to $100K Challenge event from last week.

He walks through his full approach: how he spots opportunities like this one, what signals he looks for before he acts, and how he plans his trades and how he decides how much he’s willing to risk.

Just a heads-up – we’re taking the free replay down soon, so this is last call. Again, just click here to catch the free replay of his $10K to $100K Challenge.

Coming full circle

Last week was a reminder that even the strongest investment theme can suffer steep losses when too much money crowds into the same few names. But the answer isn’t to abandon AI. It’s to be thoughtful about where and how you own it.

Eric makes the case for spreading some of your capital beyond U.S. borders. Brian offers a way to own the physical backbone of the AI buildout through Brazil, and Jonathan shows how a patient trader can approach a beaten-down AI story in South Korea.

Three different approaches, but one shared idea: the AI boom is global, and your portfolio can be, too.

We’ll keep tracking it.

Have a good evening,

Jeff Remsburg

The post Where the AI Trade Is Still Ripping appeared first on InvestorPlace.

Judging by the volatility we’ve seen in the market recently, it came right on time. 

Last week was a painful one for the technology industry. The tech-heavy NASDAQ plunged 4.5% last week, with semiconductor stocks leading the way down. 

It’s clear that folks remain concerned about how long the AI trade can last. The massive amounts tech companies are spending on AI continue to be a major concern, especially with rising interest rates. And last week’s inflation data did little to ease these concerns…

But make no mistake, it’s shaping up to be another blowout earnings announcement season.

Last week was dominated by the big banks. Bank of America Corp. (BAC), BlackRock, Inc. (BLK), Citigroup Inc. (C), Goldman Sachs Group, Inc. (GS), JPMorgan Chase & Co. (JPM), Morgan Stanley (MS) and Wells Fargo & Co. (WFC) all released results.

The reports were mixed. JPMorgan Chase and Bank of America both came up short of analysts’ top- and bottom-line expectations, while Citigroup and Morgan Stanley delivered better-than-expected earnings.

But investors were paying especially close attention to credit quality and loan-loss provisions. Wells Fargo, for example, reported lower loan losses than expected, which suggests consumer credit conditions remain relatively healthy.

Now, longtime readers know I’m generally not a big fan of bank stocks.

Bank earnings can be influenced by things like trading activity, dealmaking and changes in reserves. That makes them harder to evaluate than the companies with strong, straightforward sales and earnings growth that I typically prefer.

So, I’m not suddenly pounding the table on bank stocks. But their results still matter because they can tell us a lot about the health of the consumer and the broader economy.

But this week, things are kicking into high gear. And in today’s Market 360, I want to show you what I’ll be watching as several more market-moving companies prepare to report. Then, we’ll look at what thousands of investors are searching for in my Stock Grader AI tool and how you can use those same tools to hunt for the next earnings-season winners.

Finally, I’ll show you how I’m taking that research one step further as I search for stocks attracting big institutional money.

Earnings Season Is About to Get Much More Interesting

Our friends at FactSet currently estimate that the S&P 500 will achieve average earnings growth of 29.6% in the third quarter.

But analysts have continued to revise their earnings estimates higher.

As longtime readers know, positive analyst revisions often precede positive earnings surprises. So, I believe wave after wave of better-than-expected results could eventually push average S&P 500 earnings growth north of 33%.

And we’re about to get several important tests this week.

Netflix, Inc. (NFLX) and SpaceX (SPCX) are scheduled to report today. Then Meta Platforms, Inc. (META) and Tesla, Inc. (TSLA) are on tap Wednesday.

Those four reports should give us insight into several of the market’s biggest themes, including artificial intelligence spending, digital advertising, autonomous driving and the enormous infrastructure investments taking place in space and on Earth.

I’m also keeping a close eye on the data-storage side of the AI boom.

Western Digital Corporation (WDC) is scheduled to announce its results on Thursday. Seagate Technology Holdings plc (STX) follows next week, on Oct. 27. Both companies have benefited from booming demand for data storage as AI workloads create an ever-growing need to store and process information.

And that brings me to something interesting my team found when we looked at the latest Stock Grader AI searches (subscription required).

Investors Are Looking in the Same Places

Stock Grader AI is a new feature built on top of my Stock Grader system.

Stock Grader analyzes more than 6,000 stocks based on the factors I care about most and assigns each stock a letter grade from A to F (Very Strong to Very Weak).

Stock Grader AI adds another layer. Instead of simply looking up one company at a time, you can ask questions in plain English and screen groups of stocks by sector, industry, market capitalization and other characteristics.

And thousands of investors are doing exactly that.

From Oct. 12 through Oct. 18, more than 2,000 premium subscribers ran 7,971 searches through Stock Grader AI.

Once again, the most popular type of search was for A-rated stocks within particular sectors and industries.

But take a look at the five most-searched individual stocks:

• Micron Technology, Inc. (MU)
• Bloom Energy Corporation (BE)
• NVIDIA Corporation (NVDA)
• Dell Technologies Inc. (DELL)
• Advanced Micro Devices, Inc. (AMD)

See the pattern?

Memory. AI chips. Data centers. Power infrastructure.

In other words, investors are zeroing in on many of the same areas where corporate earnings are telling us growth remains strongest. Here’s what Stock Grader AI turned up by searching for “A-rated tech stocks”…

Of course, some of the names on this list aren’t exactly secrets. Millions of investors already know about them, Wall Street analysts cover them extensively – and every major financial network discusses them.

But there are a few that aren’t. And that’s why this tool is so handy.

It just goes to show that simply knowing where the growth is happening isn’t enough.

The real opportunity is finding the strong companies in those same booming industries before they become the stocks everybody is talking about.

Look Beyond the Obvious Names

Here’s another part of the Stock Grader AI report that caught my eye.

The second-most-popular type of search last week was for A-rated small-cap stocks, with 229 searches.

Investors were asking for things like “A-rated small-cap stocks” and smaller companies with A grades across several of my grading measures.

That’s smart. Smaller companies can sometimes benefit tremendously when a powerful investment trend accelerates.

And Stock Grader AI gives you an easy way to start looking.

You could ask it for:

“A-rated small-cap stocks.”

Or narrow things further by searching for A-rated stocks within an industry benefiting from the AI buildout.

Some investors are getting even more specific.

For example, users searched for companies with strong Earnings Revisions and Earnings Momentum.

That’s especially useful during earnings season.

After all, I don’t simply want a company that belongs to a hot industry. I want companies where sales and earnings are growing, analysts are raising expectations and institutional investors have a reason to keep buying.

That can help us move beyond the obvious stocks dominating CNBC and start building a much narrower list of fundamentally superior candidates.

Finding the Next Group of Winners

This is where Stock Grader AI becomes particularly useful.

Earnings season gives us fresh information about where corporate profits are growing fastest. Stock Grader helps us determine which individual companies have the fundamental and quantitative strength to take advantage of those trends.

And Stock Grader AI makes it easier to search through those opportunities.

But that’s still only part of my investing process.

After I identify a fundamentally superior candidate, I want to know something else: Are big institutional investors accumulating shares, or are they quietly heading for the exits?

That’s where my Precursor Intelligence, or P.I., research comes in.

Stock Grader helps me identify strong candidates. The P.I. layer lets me dig deeper into the ownership picture and look for signs that institutional money may already be moving.

And with another wave of potentially market-moving earnings reports arriving over the next several weeks, I believe understanding those institutional movements will become even more important.

In my latest presentation, I explain how I’m using P.I. alongside my quantitative research to identify stocks that could be attracting institutional buying before the rest of Wall Street catches on.

Click here to watch the presentation now and learn more.

Sincerely,

Louis Navellier

Editor, Market 360

The Editor hereby discloses that as of the date of this email, the Editor, directly or indirectly, owns the following securities that are the subject of the commentary, analysis, opinions, advice, or recommendations in, or which are otherwise mentioned in, the essay set forth below:

Advanced Micro Devices, Inc. (AMD), Bloom Energy Corporation (BE), Dell Technologies Inc. (DELL), Micron Technology, Inc. (MU), NVIDIA Corporation (NVDA), Seagate Technology Holdings plc (STX), Western Digital Corporation (WDC)

The post The Best Place to Find the Next A-Rated Earnings Winners appeared first on InvestorPlace.

This Week’s Ratings Changes:

Upgraded: Strong to Very Strong

Downgraded: Very Strong to Strong

Upgraded: Neutral to Strong

Downgraded: Strong to Neutral

Upgraded: Weak to Neutral

Downgraded: Neutral to Weak

Upgraded: Very Weak to Weak

Downgraded: Weak to Very Weak

To stay on top of my latest stock ratings, plug your holdings into Stock Grader, my proprietary stock screening tool. But, you must be a subscriber to one of my premium services.

If you are a member of one of my premium services, you can go here.

Sincerely,

Louis Navellier

Editor, Market 360

The post Allstate Upgraded, Dell Technologies Downgraded: Updated Rankings on Top Blue-Chip Stocks appeared first on InvestorPlace.

It bought Nscale a plot of land in Loughton, a quiet commuter town on the eastern edge of London. It bought a lease commitment from Microsoft (MSFT), the deepest-pocketed anchor tenant on Earth. It reserved 23,040 of Nvidia‘s (NVDA) top-shelf GB300 chips – silicon that entire nations are lobbying to get their hands on.

The one thing it couldn’t buy was electricity.

Over the weekend, news broke that Microsoft has walked away from its deal to lease Nscale’s planned 50-megawatt data center at its Loughton site. The facility was supposed to go live around the end of this year. The timeline slipped. Then, according to reporting from the Telegraph, grid officials delivered the news that no amount of capital could fix: sufficient power might not reach the site until the 2030s.

The chips and the customer are ready and waiting. The demand, as we’ll see in a moment, is so intense that Microsoft is signing multi-billion-dollar compute deals as fast as it can. And yet a marquee AI project on the outskirts of one of the world’s great financial capitals just stalled for want of electrons – with a wait measured not in quarters but in presidential terms.

We think this story is one of the most instructive AI headlines of the year.

Why Microsoft Walked Away From Nscale’s Loughton Data Center

Nobody canceled the AI boom this past weekend.

Nscale says it remains committed to the Loughton project, is exploring alternative power sources for the site, and that its other contracts with Microsoft are unaffected. Microsoft, for its part, says the decision concerns this single site and that its broader partnership with Nscale is strong. 

What happened in Essex is narrower and more interesting: a sophisticated buyer looked at a facility with land, chips, and capital all secured – and deemed that without a reasonable path to power, none of the rest counted.

The episode stings extra for Nscale because the company is preparing for a U.S. IPO, with Microsoft and Anthropic making up the bulk of its contracted business. Bloomberg has reported that its flagship facility in Narvik, Norway, is running about six months behind schedule, with just 6.4 megawatts of a planned 30 live so far. 

That makes Nscale a great case study in the defining gap of this phase of the AI trade: between announced megawatts and powered ones.

The AI Data Center Bottleneck Is Moving to the Grid

Delivering them can take most of a decade. And it’s inside that mismatch that the real AI infrastructure story is playing out.

Across the industry, hyperscalers plan to pour roughly $400 billion into terrestrial data centers in 2026 alone. New announcements arrive weekly – gigawatt campuses, sovereign AI zones, “Stargates” of every nationality. 

Meanwhile, as far as substations and transmission lines go, interconnection queues in Northern Virginia, California, and Germany now stretch seven to 12 years. U.S. data centers are on track to add 240 terawatt-hours of electricity demand by 2030, and utilities are fielding connection requests that, together, exceed anything the grid has absorbed since the introduction of air conditioning.

And before a single AI workload can come online, every planned campus has to survive the same gauntlet: find the site, win the permits, lock in a grid-connection date that doesn’t drift into fantasy, arrange backup or onsite generation, and build out the cooling. Only then does ‘capacity’ mean anything at all.

Capital clears the first hurdle easily. Chips clear the second. 

But electricity doesn’t care how much of either you have. The queue is the queue. Loughton just showed us what happens when the line is a decade long.

Microsoft Is Still Buying AI Capacity – Just Somewhere Else

While backing out of the powerless site, Microsoft has committed to a deal with the very same company worth up to $14 billion for roughly 200,000 Nvidia GB300 chips across other locations. 

The centerpiece: about 104,000 GPUs headed to a 240-megawatt campus in Texas – a site leased from a Bitcoin-miner-turned-data-center operator, designed to scale toward 1.2 gigawatts, with an option for 700 more megawatts by late 2027. Another tranche lands at the Start Campus in Sines, Portugal, a site built alongside dedicated power and subsea cables.

So, what did those sites have that Essex didn’t? Texas, with its fast-moving, generation-rich grid. A Portuguese campus engineered around energy access from the jump. Sites with existing industrial power infrastructure, inherited interconnections, or their own generation.

When Loughton stalled, demand simply relocated – flowing, like water, toward wherever the electrons already were. That is what will separate the AI infrastructure players into two groups: those holding press releases, and those holding power.

4 Data Center Power Stocks Positioned Around the Bottleneck

If powered capacity is the AI boom’s scarce commodity, then the companies that create it collect the toll – regardless of which hyperscaler or GPU cloud wins any individual lease.

These are the names we keep coming back to:

• Eaton (ETN) supplies the electrical backbone of the modern data hall – switchgear, distribution, power management – and has been working directly with Nvidia on reference designs for AI-era facilities. When a campus does secure its megawatts, Eaton gear is frequently what carries them to the racks.
• GE Vernova (GEV) sits even further upstream, selling the turbines and grid equipment that create and move power in the first place. In a world where developers increasingly bring their own generation rather than wait a decade in a queue, the makers of that generation hold rare pricing power.
• Vertiv (VRT) owns the inside of the building: power conditioning, backup systems, and the liquid cooling that dense GB300-class deployments demand. Its order book has become a proxy for real – not merely announced – buildout: the company exited 2025 with a record $15 billion backlog, more than double the year before, booking nearly three dollars of new orders for every dollar it shipped.
• Quanta Services (PWR) is the one actually stringing the wire. Transmission lines, substations, electrical construction at scale – the unglamorous work every stalled project on Earth is waiting for. Its acquisition of Cupertino Electric plugged it directly into the technology sector’s buildout.

Each of these, of course, are thematic exposures rather than automatic buys. Several have run hard as the market wakes up to the power trade, and each carries its own project-timing and valuation risks. 

The more important point of this watchlist is the pattern behind it: whoever controls the narrowest point in a supply chain ends up pricing everything that flows through it.

The Bottom Line: Powered Megawatts Are Becoming AI’s Scarce Asset

In its first act, the AI trade rewarded whoever had the chips. Its second act will reward whoever can plug them in.

What died in Loughton wasn’t a data center – the site may well get built eventually. What died was an assumption, one still embedded in hundreds of glossy announcements worldwide: that the electricity will simply show up when the servers do. Microsoft’s decision shows that even the deepest-pocketed AI buyers may walk away when a credible path to power disappears.

It won’t be the last. The investors who internalize that earliest will own the choke point while everyone else is still reading press releases.

Where AI Goes When the Grid Can’t Follow

Which brings us to the question we’ve spent much of this year chasing: if the grid can’t carry where AI is headed… what can?

That question sits at the center of a project I call “XPANSE.” And unlike the stalled announcement we just walked through, this one is being built with real money, right now.

Consider what SpaceX (SPCX) disclosed in its first earnings report as a public company: $15.8 billion poured into its AI buildout in a single quarter, on a capacity schedule – roughly two gigawatts of compute this year, approaching ten by the end of 2027 – that no developer stuck in an interconnection queue could dream of matching. 

While the rest of the industry waits a decade for a substation, Musk isn’t asking the grid for permission. He’s routing around it entirely.

The modern economy currently balances on two single points of failure: advanced chips concentrated on one island in the Taiwan Strait, and electricity trapped in decade-long queues. XPANSE, as I see it, is Musk’s answer to both.

So, my team and I spent months tracing where those billions actually land – the suppliers, the enablers, the publicly traded companies catching money that’s already in motion. In my new briefing, I walk through the three moves that follow from that map, starting with one company sitting squarely at the center of it all, whose name and ticker symbol I’ll give you for free, just for watching.

The grid queue may be a decade long; but the window to get positioned isn’t.

Watch the full XPANSE briefing now.

The post Microsoft’s 23,040-Chip Data Center Stalled on a Power Problem appeared first on InvestorPlace.

As I write on Monday morning, the AI trade is trying to claw its way back after last week’s brutal selloff.

But whether this is a fool’s gold rally or the start of a real bull run into the end of the year, one thing is true: AI itself is quietly eroding the business models of some of the market’s best-known companies. It’s critical that you and I recognize how this is happening and prepare our portfolios – not just for a week of volatility but for permanent existential risk.

For an example that’s playing out right now, let’s rewind 26 years…

In September 2000, the founders of a money-losing DVD-by-mail startup flew to Dallas to pitch the CEO of the biggest name in home video on an acquisition.

The startup was Netflix (NFLX). The CEO was Blockbuster’s John Antioco. And the asking price was $50 million.

Netflix co-founder Marc Randolph, who showed up in shorts, a tie-dyed T-shirt and flip-flops, later described the moment the number landed. As he put it in his memoir, “John Antioco was struggling not to laugh.”

Blockbuster turned down the deal, and 10 years later, it filed for bankruptcy.

It’s become the business world’s favorite cautionary tale about a dominant company that didn’t see what was coming. But today, the story is worth retelling for an ironic reason…

Netflix may be staring down its own Blockbuster moment – though for a very different reason.

The streaming giant stumbles

Last Wednesday, Netflix management told employees it will lay off roughly 6% of its workforce, or about 1,000 people. The cuts land mostly on the product, tech, legal and HR teams.

A few weeks ago, co-CEO Ted Sarandos told a Bloomberg conference that the company was “not growing as fast as I want.” As one illustration of this, viewing time grew just 2% in the first half of the year.

Wall Street has noticed. In June 2025, NFLX stock hit a record high. But as I write on Monday, it trades at less than $70 – down nearly half since that high-water mark.

But this selloff is less about an upstart company challenging the industry king, and more about an upstart technology challenging the entire model.

Netflix sees AI coming. In fact, it’s embracing it. Last year, Netflix confirmed that its Argentine sci-fi series The Eternaut featured the first generative AI footage ever to appear in the final cut of a Netflix original.

The scene showed a building collapsing in Buenos Aires. Sarandos told analysts the sequence was finished 10 times faster than with traditional visual effects. He added that, without AI, the cost “would just not have been feasible for a show in that budget.”

But look at the flip side of that – the same tool that lets Netflix make an expensive scene cheaply lets everyone make it cheaply. And that dovetails into the problem…

For two decades, Netflix’s moat rested on a simple fact: great video is expensive and slow to make, and Netflix could outspend nearly everyone. Blockbuster’s downfall was a failure of vision. Netflix faces something more difficult: a technology that erodes its moat, no matter how clearly management sees the danger coming.

“Nothing is happening at all” –until it is

Tom Yeung, lead analyst for our global macro expert Eric Fry in Fry’s Investment Report, has been tracking this threat since March.

Back then, Netflix traded near $100, and investors weren’t worried about its long-term profits. After all, AI video was still mostly a punchline.

Here’s how Tom described AI video quality at the time:

A recently generated viral clip of Jackie Chan fighting Jet Li had more bugs than a picnic in July.

Anyone watching it carefully will notice the kung fu actors reaching straight through objects, growing phantom limbs, and magically teleporting between camera shots.

Then the situation changed, gradually at first and then all at once.

Back to Tom:

In short, people saw the technology the same way parents often view their kids – with progress so gradual that it’s tempting to conclude that nothing is happening at all.

But every once in a while, there comes an epiphany of how far things have come. For AI-generated video, that realization happened over the past six months after a stream of new developments began making headlines.

Two of those developments came from China. First, in April, regulators approved the world’s first theatrical release of a feature-length AI film by a major mainstream movie studio. That film, Sanxingdui: Future Memories, opens in Chinese theaters this Friday.

Then in August, a Chinese company began releasing episodes of an AI-generated TV show, The Sequel to Journey to the West. Tom notes that it racked up 280 million views across its first five episodes and ranked No. 1 among some provincial channels.

The economics behind all this are startling…

According to Chinese state broadcaster CCTV, the cost of producing one minute of an AI short drama fell from 5,000 yuan (about $700) to just a few hundred yuan in the first half of this year.

One Chinese director said a wedding scene that would have cost him about $9,000 to shoot cost about $210 with AI.

Circling back to Netflix, here’s Tom with the fallout:

Shares of Netflix have since fallen below $70, and one analyst even dared put a “Sell” rating on this formerly blue-chip stock – its first negative review since the start of the year.

After all, Netflix is now facing some real competition.

Credit to Tom – Wall Street’s first bearish call (last month) arrived after the stock had already fallen about 30% from Tom’s March warning.

In fairness to Netflix

Before we write Netflix’s obituary, a real bull case remains.

Netflix has more than 300 million subscribers, and its advertising revenue is on track to roughly double this year, to about $3 billion. Meanwhile, management has guided to $51 billion to $51.4 billion in 2026 revenue.

Plus, live sports and events, which AI can’t fake, are a growing part of the mix. And AI may cut Netflix’s own production costs as much as anyone’s.

These tailwinds mean investors trying to understand whether AI will hurt or help Netflix should ask two questions…

What is Netflix’s core asset as a company? And does AI make that asset more or less scarce?

If it’s the content, Netflix’s dominance looks shaky as a wave of cheap content is coming. But if it’s the subscriber relationship and global distribution network, the moat may hold.

Notably, CNBC reports that Netflix’s biggest threat has been YouTube, which is a distribution platform rather than a studio. YouTube doesn’t need to make the best shows. It wins by being the viewing channel people turn to by habit.

That’s a hint that in a world of abundant video, the scarce asset is the platform where viewers spend their time – and with more than 300 million subscribers, Netflix owns one of the biggest. The catch is that Netflix is competing with YouTube for those same hours – and YouTube is free to watch.

Now, beyond Netflix, the question of “what’s actually scarce?” is critical to ask as you evaluate your portfolio – after all, it’s how we spot small cracks in our own holdings before they turn into massive fissures.

Two ways AI breaks a moat

Netflix’s challenge – that something which once made it valuable is becoming abundant – isn’t unique. Plenty of good businesses will face it in the years ahead.

This points to two tests we can run on every stock we own…

The scarcity test.

Pricing power follows scarcity. When AI turns a scarce thing into an abundant thing, the pricing power leaks away, even from well-run companies.

The logic applies to any business whose core product is expensive, skilled human output. That includes tutoring and homework help, stock photography, call-center labor and ad production.

So, does AI make the products of the companies you own more or less scarce?

The friction test.

In our Sept. 29 Digest, we looked at how AI agents like Meta Platforms Inc.’s (META) Muse could commoditize businesses built on customer inertia. These include banks paying 0.1% on checking accounts, insurers counting on lazy renewals, and wireless carriers charging loyal customers more than new ones.

Scarcity and friction are two different mechanisms with one shared outcome: margins that looked permanent can turn out to be temporary.

So, does AI make it easier for customers to find better or cheaper alternatives to the products and services offered by the companies you own?

If the answer is “yes” to either of these two tests, be careful.

When to act: Eric Fry’s rule

The problem for investors is that by the time disruption is obvious, it’s usually priced in. Tom issued his warning in March. Wall Street’s first sell call arrived in September – 30% lower.

Eric – our macro investing expert – has a rule for exactly this kind of situation. Now, to be clear, he wasn’t writing about Netflix. He was writing about risk in the broader market. But the point remains:

Panic early. That’s the only near-certain defense against adversity in the financial markets, and in life generally…

Once you catch a whiff of smoke from a distant wildfire, you don’t hang around until embers are landing on your roof…

Successful panicking begins by saying “no” to obvious risks. Only then can you calmly examine and select opportunities that offer a more favorable route to wealth-building.

Panicking early doesn’t mean dumping every stock that AI touches. It does mean assessing the situation soberly, then making calm, deliberate choices.

For more on the stocks that Eric believes are worth holding today, click here to learn about joining him and Tom in Fry’s Investment Report.

Coming full circle

This brings us back to Netflix, which reports earnings tomorrow.

If you own the stock, this will be a live test of what Netflix’s core asset really is. Watch engagement trends, content spending, and anything management says about generative AI in production.

Strong engagement and a growing ad business would suggest the subscriber relationship is the scarce asset that holds. Another quarter of flat viewing would point the other way.

Either way, let’s not miss the wider point…

Netflix beat Blockbuster by making video easy to get. The next disruption is making video easy to make. Unlike Blockbuster, Netflix sees it coming. What’s still unclear is whether that’s enough.

Now, before we wrap up today, a quick related note…

Want to trade Netflix’s earnings tomorrow but aren’t sure about which way it will break?

If you’re tempted to trade Netflix’s earnings, you don’t necessarily have to correctly predict which way the stock will move to make money.

I learned that from veteran trader Jonathan Rose, editor of Advanced Notice. Sometimes, instead of betting on the direction a stock will move after an earnings report, Jonathan buys both calls and puts – positioning to profit from a big move, whichever way it goes.

Under the right circumstances, it can be very lucrative…

For example, this approach paid off for Jonathan’s subscribers last week with FMC Corp. (FMC). Shares plunged more than 36% after a dramatic guidance cut, and Jonathan’s subscribers took profits on the put side for what he called “more than 200% on our total position.”

For more on how Jonathan finds and structures trades like this – plus his entire trading approach to the markets – you can still catch a free replay of his $10K to $100K Challenge from last week. We’re taking the replay down later this week, so click here to watch it while you can.

We’ll keep tracking Netflix here in the Digest.

Have a good evening,

Jeff Remsburg

The post Netflix’s Moat Is Disappearing. Is Yours? appeared first on InvestorPlace.

And given the market turbulence we’ve seen lately, it’s easy to understand why investors might be feeling uneasy.

We’ve had a sharp sell-off in tech stocks, stubborn inflation, rising oil prices and plenty of uncertainty about the Federal Reserve’s next move.

But what if I told you that October is actually one of the best times of the year to buy stocks?

That’s exactly what my friend Jeff Hirsch believes.

Jeff Hirsch is the editor-in-chief of The Stock Trader’s Almanac, which has spent 60 years tracking seasonal market patterns and uncovering some of Wall Street’s most interesting historical trends.

And according to Jeff, October has historically been the strongest month for the S&P 500 during mid-term elections. In fact, he believes we’re entering what he calls the “sweet spot” of the four-year presidential election cycle, a period that has historically produced some of the market’s strongest gains.

Better yet, his seasonal buy signal has already flashed.

Now, that doesn’t mean stocks will go straight up from here. But he believes the stage is set for stocks to move higher into year-end, and well into 2027.

That’s why I asked Jeff to join Crystal and me on this week’s Navellier Market Buzz.

We discuss why tech and small-cap stocks could lead the next rally, the latest inflation readings and how they impact the bond market, why he believes we’re still early in early stages of an AI buildout – and three stocks he’s watching now.

Click the image below to watch this week’s Navellier Market Buzz.

How to Find Bigger Gains in a Volatile Market

Interestingly, while we’re seeing the potential for a short-term rally heading into the end of the year, the swings along the way could set up new opportunities of their own, if you know where to look…

My colleague Jonathan Rose knows a thing or two about finding them – especially in bumpy conditions like we’ve seen lately.

Jonathan spent eight years trading in the Chicago pits, where he learned to track the movements of Wall Street’s biggest players.

So, when tech stocks recently hit near record highs while bond prices were falling, the disconnect caught his attention.

He warned that the Nasdaq could drop 5% over the short-term –  which is close to what happened.

And when asked what he’d do if that played out, he was unequivocal: “Back up the truck and let’s buy.”

He didn’t mean to buy everything that goes on sale, of course.

Jonathan watches for unusually large trades that could signal someone is putting serious money behind an idea. As he explains, a million-dollar order in NVIDIA Corporation (NVDA) might barely stand out. But the same order in a smaller, less heavily traded company could deserve a closer look.

Jonathan explains how he puts all the pieces together in his free $10K to $100K Challenge.

He walks through how he identifies unusual trading activity, evaluates opportunities and structures positions with a defined amount at risk.

And he shows you just how he’s used that strategy to identify some remarkable opportunities, including:

• 209% in just 13 days from Lyft, Inc. (LYFT)…
• 183% in 14 days from QXO, Inc. (QXO)…
• And 275% in less than a month from iShares Ethereum Trust ETF (ETHA).

Of course, not every trade will be a winner. But these examples show just how quickly gains can add up when you identify the right opportunity.

Now, in his latest presentation, Jonathan explains how he believes it’s possible to turn $10,000 into $100,000 over 12 months with this strategy.

It’s an ambitious goal, to be sure. But if you’d like to learn how Jonathan finds these opportunities, I encourage you to watch while you have a chance.

Click here to watch Jonathan’s free $10K to $100K Challenge presentation now.

Sincerely,

Louis Navellier

Editor, Market 360

The post The Stock Market’s Sweet Spot Starts NOW (3 Stocks to Buy) appeared first on InvestorPlace.

Now we’re seeing that volatility arrive.

I’m not here to tell you to run for cover. I’m looking for opportunities, and I’ve got an interesting way of deciding when to act. I recently explained that approach in my free $10K to $100K Challenge presentation, which is now available to watch on demand.

Today, I’m sharing my take on the selloff, three companies I’m watching, and what I’m waiting to see before making my next move.

Here’s that link to the replay again

About a week ago, I told my colleague Jeff Remsburg that this darn bond market is scaring me. Maybe you saw it in the Digest.

Stocks were near record highs, but bond prices were falling, yields were climbing, and the two markets were telling very different stories. I spent eight years trading bonds in the Chicago pits, and when I see that kind of disconnect, I pay attention.

I told Jeff I wouldn’t be surprised to see the Nasdaq drop 5%.

Well, here we are.

As I write this Friday afternoon, the Nasdaq Composite is already down about 4.5% for the week. Tech stocks are getting hammered. Investors are suddenly asking hard questions about the billions being borrowed to finance the AI boom.

Meanwhile, the Dow Jones Industrial Average is actually up a little for the week. That tells me money isn’t simply leaving the stock market. Some of it is moving elsewhere.

And here’s the part that might surprise you.

When Jeff asked what I’d do if the Nasdaq fell 5%, I didn’t hesitate. I said, “Back up the truck and let’s buy.”

I meant it.

But I didn’t mean buy everything. And I certainly didn’t mean chasing the first stock that looks cheap.

I’ve got a short shopping list (and I’ll share three of the stocks on it with you below). And I’ve got a particular way of deciding when it’s time to act.

Let me explain…

What the Bond Market Is Telling Me

First, a little background on why bonds have me so nervous.

When bond prices fall, their yields rise. That means investors are demanding more compensation for lending money. And higher borrowing costs can create problems for companies that depend on debt to finance their operations.

That’s especially true for smaller companies.

In my conversation with Jeff, I pointed out that the Russell 2000 small-cap index was looking particularly weak compared with the Nasdaq. A large percentage of those smaller companies have floating-rate debt, which means their borrowing costs can rise along with interest rates.

That’s not a great combination.

But something interesting happened this week.

As tech stocks began selling off, investors started buying U.S. Treasury bonds again. Treasury yields fell, even after another hot inflation report.

At the same time, the bonds of some heavily indebted AI companies continued getting crushed.

Take CoreWeave Inc. (CRWV). Yields on some of this data center operator’s bonds recently approached 15%. That’s the credit market sending a warning: Investors are demanding a whole lot more compensation for the risk of lending CoreWeave money.

So we’re seeing two things at once: Investors are seeking safety in government bonds while becoming increasingly nervous about companies borrowing enormous amounts to build AI infrastructure.

To me, that’s another reason to be selective.

I’d say I’m bullish going into the end of the year. But I expect volatility, and I don’t think every company is going to participate equally when the market recovers.

Which brings me to my shopping list.

Three Stocks I’m Watching

I’ve got three companies on my radar right now.

The first is Freeport-McMoRan Inc. (FCX). Freeport is one of the world’s major copper producers, and I’ve been talking about copper as an AI bottleneck for a while now.

Think about what goes into building all these data centers. You need chips, sure. But you also need enormous amounts of electrical infrastructure to power and connect everything.

And that requires copper. The world doesn’t have unlimited copper supplies, and bringing new mines online takes years.

When I spoke with Jeff, Freeport was trading roughly 10% below its highs, even though copper prices were near their highs. That’s an interesting disconnect.

Freeport has also been recovering from problems at one of its major mines. I think that gives us a company worth watching as copper demand continues to grow.

My next two names come from the space business.

AST SpaceMobile Inc. (ASTS) is developing a satellite network designed to connect directly with ordinary mobile phones.

And Rocket Lab Corp. (RKLB) builds and launches rockets while also supplying equipment and systems for space missions.

I like both companies because I think the space industry has a long runway ahead of it.

However, these space stocks can be incredibly volatile. During my interview with Jeff, I pointed out that AST SpaceMobile had recently gained about 9% one day and was down roughly 7% the next.

That’s not unusual for these names. And it’s why I don’t want to chase them when everybody’s excited.

If the Nasdaq gets hit and drags these companies down with it, I want to be ready.

But having a list of stocks I like is only half the job. The other half is figuring out when there’s actually a trade worth making.

And that’s where my years on the Chicago trading floor come in.

The Lesson I Learned From the Best Traders in Chicago

When I first started trading in Chicago, I came in cocky. Made a bunch of easy money.

But you know what came next: I pretty quickly figured out I had a lot to learn.

One of the most valuable lessons came from watching the traders who consistently made money.

You know what surprised me most? A lot of them spent most of their time doing absolutely nothing.

They weren’t jumping into every little move or trying to predict where every stock would go next. They waited.

Then, when a really big order came into the market, they’d pay attention. They knew somebody was putting serious money to work.

And when that kind of money starts flowing into a stock, it can move the market.

That’s something I’ve carried with me ever since. Today, I look for unusually large trades, especially in companies that aren’t already attracting enormous trading volume.

A million-dollar trade in Nvidia Corp. (NVDA) might be just another Tuesday. But a million-dollar order in a smaller company that doesn’t normally see that kind of activity gets my attention.

I don’t automatically make a trade, but I start investigating.

Maybe there’s an upcoming catalyst. Maybe institutions are starting to build positions. Maybe something is changing in the business that the broader market hasn’t fully appreciated.

That’s the advantage I’m looking for.

And it’s why my shopping list matters.

I already know I like copper and space. I already know which companies interest me.

Now I can watch them for unusual trading activity that might help me identify an attractive opportunity.

The Other Half of a Good Trade

Of course, spotting an opportunity doesn’t do you much good if you don’t know how much you’re willing to lose.

That’s another thing I learned on the trading floor. You can’t control what the market does after you enter a trade, but you can control how much money you put at risk.

Here’s a simple example.

Suppose I find a trade I like. Each contract costs $50. I could buy 10 contracts for $500.

But what if I’m only comfortable risking $200? Then I buy four contracts instead.

That’s it.

With a straightforward trade like that, my maximum loss is the premium I paid. In this example, $200, plus transaction costs.

I don’t need to hope I can get out before the market moves against me. I’ve established my maximum loss before entering the trade.

And if the stock makes a big move in my favor, the trade can potentially deliver a much larger percentage gain than owning the shares outright.

Of course, if the trade doesn’t work, you lose the whole premium. That’s it. That’s your max loss.

That’s why position sizing matters so much. I’ve seen plenty of traders make a correct prediction and still lose money because they picked the wrong trade or took too much risk.

And I’ve seen traders turn a relatively small investment into a substantial gain because they waited for the right opportunity.

Being right about a stock is only part of the job. Getting the trade right matters just as much.

What I’ll Do if the Nasdaq Keeps Falling

So let’s return to that conversation with Jeff.

The bond market was scaring me. I thought the Nasdaq could fall 5%. And when Jeff asked whether I’d buy that decline, I told him to back up the truck.

I wasn’t kidding.

But that doesn’t mean I’m putting all my money into the market the moment the Nasdaq hits some arbitrary number. I’m watching how money moves between stocks and bonds. I’m watching which sectors hold up when the market gets ugly.

And I’m watching the market for the big, unusual trades that tell me somebody is putting serious money behind an idea.

Freeport-McMoRan, AST SpaceMobile, and Rocket Lab are three of the names on my list. But they’re not automatic buys. When I see an opportunity, I’ll decide how much I’m willing to risk before putting a dollar to work.

That’s the approach behind my $10K to $100K Challenge.

In the free presentation, I explain how I identify unusual trading activity, how I evaluate potential trades, and how I structure positions to pursue large gains while keeping my maximum risk defined.

The goal is ambitious: exploring whether it’s possible to turn $10,000 into $100,000 in 12 months. There’s no guarantee of reaching it.

But you can learn the process I use to look for opportunities, and you don’t need to wait for the Nasdaq to fall another 5% to start learning.

Watch my free $10K to $100K Challenge presentation here.

The bond market still has my attention.

And if this selloff gives me a chance to buy companies I like at better prices, I’ll help my members put together some low-risk, high-reward trades.

I’ve already got my shopping list. Now I’m waiting for the right moment.

The creative trader wins,

Jonathan Rose

Founder, Masters in Trading

The post The Bond Market’s Warning – and Three Stocks Worth Watching appeared first on InvestorPlace.

There is a common pattern in new technology cycles, and it goes like this: 

The innovation itself appears. Then, a bottleneck emerges. Next, capital floods in to solve the problem. Finally, the regime changes.  

We saw this “regime change,” or complete reorganization of stock market winners and losers, in the dot-com bust phase. 

Capital rotated out of the high-profile names and into a variety of other sectors, including base metals, precious metals, energy insurance, and utilities. Those sectors delivered solid double-digit or triple-digit returns over the early part of the 2000s, even while the Amazons, Intels, and Ciscos of the world fell 80% or more. 

Another regime change is happening now.  

Since the early AI revolution, the Magnificent Seven companies have been sat securely on the throne. The group includes Alphabet Inc. (GOOGL), Amazon.com Inc. (AMZN), Apple Inc. (AAPL), Meta Platforms Inc. (META), Microsoft Corp. (MSFT), Nvidia Corp. (NVDA), and Tesla Inc. (TSLA).  

But their seat is soon to be usurped. We are starting to see a rotation out of some of the highest profile, high beta tech stocks and into more real-world, asset-backed sectors. 

This dynamic will only increase as we move forward. That means it’s important to own the companies that are providers or suppliers to this massive AI buildout, rather than the companies that are spending the money to build. 

I’ll share one of my favorite stocks that is significantly outperforming the Mag 7 so far this year. But first, let’s take a look at what we covered at Smart Money last week.

Smart Money Roundup

October 15, 2026

The AI Bargain Hiding in Big Pharma

Investors may not be giving big pharma companies credit for the potential to turn AI-driven innovation into stronger growth and profits. Let’s discover this bargain hiding in plain sight…

October 17, 2026

Why Playing It “Safe” With U.S. Stocks Could Backfire

Overconfidence can lead investors to favor U.S. stocks even when foreign markets offer compelling alternatives. So, I’ll walk you through the hidden risks of sticking with the status quo, and point you toward several overseas opportunities I’m backing that most U.S. investors overlook.

October 18, 2026

The AI Selloff Is Sending Investors a Warning, and Here’s Where to Look

Back in August, my colleague Jonathan Rose warned about two AI favorites, CoreWeave, Inc. (CRWV) and Oracle Corp. (ORCL). Both stocks have since taken a beating. Here’s Jonathan with the story of what he saw coming – and what investors can learn from it.

Mag 7 Killer: A Prolific Energy Producer 

One of my favorite Mag 7 killers is one of America’s most prolific energy producers, and it’s firmly positioned to fuel America’s AI buildout. Data center demand for natural gas could become especially acute in the Delaware Basin, with a new “Data Center Alley” potentially blossoming in the region. 

As one of the leading producers in the Delaware Basin, Devon Energy Corp. (DVN) is well-positioned to benefit from structurally improving pricing trends in the region. 

For the last few years, the Delaware Basin has been rapidly boosting its production of both oil and gas. Unfortunately, gas volumes have overtaken pipeline capacity. As a result, much of the gas from the Delaware Basin is “stranded” – the oil and gas industry’s polite way of saying “worthless unless you can move it.” 

Producers flared it. Trucked it. Discounted it to oblivion. As such, the Delaware Basin has behaved for years like a brilliant student stuck in detention. It held enormous potential, but had no way to express it. 

But detention is ending. Two major pipeline projects are improving the economics of the Delaware Basin, especially for Devon. 

At the start of this year, Wall Street analysts expected Devon Energy to earn roughly $3.95 per share in 2026. Today, their consensus estimate is around $5.40 – an increase of nearly 37%. Devon shares have also climbed substantially this year, but earnings expectations have risen even faster.

Therefore, even though Devon shares have advanced 26% this year, the company’s expected earnings have increased even more.

Regards,

Eric Fry

The post The AI Trade Is Changing, and This Energy Giant Is Ready appeared first on InvestorPlace.

Jonathan recently revealed how he uses options to pursue extraordinary gains in his free $10K to $100K Challenge presentation. I encourage you to watch it. But first, here’s Jonathan with the story of what he saw coming – and what investors can learn from it.

Hey, guys.

In October 2015, a natural gas well near Los Angeles started leaking methane.

And I don’t mean a little leak. This thing was a catastrophe.

The leak came from an underground storage facility tucked into the mountains just above LA’s sprawling San Fernando Valley. Soon, a rotten-egg stench was drifting through nearby neighborhoods.

Residents reported headaches, nausea, and nosebleeds. Thousands of families fled to hotels and temporary housing, with no idea when they could return. Two local schools had to be relocated.

The leak wouldn’t be stopped for 111 days.

But something about the coverage bothered me. Every article talked about Southern California Gas Co.

OK. But I had an additional question: Who owned SoCalGas?

Turns out the parent company was Sempra (SRE), a publicly traded utility.

I pulled up Sempra on my screener and found something that stopped me cold. Somebody had made an unusually large bearish trade against the company.

I had two pieces of information: a major environmental disaster involving a Sempra subsidiary… and a big bearish trade in the parent company’s stock.

I didn’t know who placed that trade or what they knew. But I’d spent years trading on the floors of the Chicago exchanges, where I learned to pay attention when large trades show up in unusual places.

Somebody was putting real money behind a bet that Sempra was going lower.

So I shared a bearish trade of my own with my followers. With it, we risked $200 for the opportunity to make $4,800.

A few days later, California declared a state of emergency, and Sempra’s stock plunged. One of my followers later told me he’d made $9,600 after risking $400.

Here’s another part I love.

I found a reporter covering the leak who hadn’t mentioned Sempra, so I reached out and pointed out that SoCalGas had a publicly traded parent company. She wrote back that she was working on a follow-up.

That’s what I mean when I talk about following the money.

While everybody was watching the gas leak, I was watching the company behind it – and what traders were doing with its stock.

This August, I spotted something similar in a very different business: artificial intelligence.

Two AI Stocks I Didn’t Want to Own

On August 17, I was hosting my daily Masters in Trading LIVE show. We were talking about retail earnings and consumer health.

Then I changed the subject to two AI companies that had me worried: CoreWeave Inc. (CRWV) and Oracle Corp. (ORCL).

Now, I’m still very bullish on AI. I love what Nvidia Corp. (NVDA) is doing. I think artificial intelligence will create enormous opportunities for years to come.

But that doesn’t make every AI company a good investment.

CoreWeave and Oracle were borrowing enormous amounts of money to build AI infrastructure.

CoreWeave rents computing power to AI companies. That means buying expensive chips, building data centers, and spending a fortune before all that equipment generates revenue.

Oracle is making its own enormous investments in AI data centers, with a substantial portion of its future business tied to OpenAI.

Then there’s what’s called “circular financing.”

Nvidia sells chips to CoreWeave. Nvidia also owns a stake in CoreWeave. AI companies sign massive agreements to rent computing capacity. The companies providing that capacity borrow money to buy more equipment.

Everybody announces another billion-dollar deal, and investors get excited.

But I have a question: Where is all this money actually coming from?

When companies borrow billions and funnel money among the same group of businesses, those impressive deals can conceal a great deal of financial risk.

That’s why I called my August 17 show the AI House of Cards.

I told viewers that if the market turned, CoreWeave and Oracle would be among the first companies to get hit. I didn’t want to be long either stock. In fact, I suggested CoreWeave shareholders consider taking their profits.

CoreWeave was trading around $106 when I issued my warning.

Things Get Interesting

Now, I need you guys to stay awake for a minute. I’m going to talk about bonds.

I know, I know. Everybody’s favorite subject.

But this is important.

Most investors watching CoreWeave were looking at the stock price, Nvidia, and all those enormous AI deals. I was looking at what it cost CoreWeave to borrow money.

CoreWeave had issued bonds paying 9.6% interest, but those bonds were now trading at prices that pushed the yield to around 15%. That’s a massive jump.

That means investors were demanding much more compensation to take on CoreWeave’s risk. Somebody was getting nervous. And the warning appeared in the debt market before it became obvious in the stock price.

Oracle was showing warning signs, too. The cost of insuring its debt against default had risen sharply.

When you’re borrowing billions to build data centers, the cost of money matters. And when lenders get nervous, stockholders had better pay attention.

What Happened After My Warning

On October 15, I revisited CoreWeave and Oracle during Masters in Trading LIVE.

CoreWeave had fallen from approximately $106 on August 17 to around $61. That’s a decline of roughly 42% in less than two months.

Oracle had taken a beating, too. Other AI infrastructure names were under pressure.

The immediate trigger wasn’t necessarily a new discovery about AI. Hotter-than-expected inflation raised concerns about interest rates and borrowing costs.

And companies carrying enormous financial obligations were particularly vulnerable. That’s what worried me in August.

Look, CoreWeave has real customers and an enormous backlog of contracted business. Some investors see a tremendous opportunity after this decline.

Fine.

But there’s a difference between having billions in business lined up and having the financial strength to deliver it profitably. And when you borrow heavily to fund growth, you don’t have much room for things to go wrong.

Here’s another thing I told viewers on Thursday. I wouldn’t make a new bearish trade on CoreWeave at $61.

The stock has already been punished. Could it go lower? Absolutely. But a good warning in August doesn’t automatically make it a good bearish trade in October.

Being right about the problem doesn’t automatically make every price a good place to bet against it. The trade has to make sense too.

That’s why I always want to know my risk before entering a trade.

What the Big Money Is Telling Us

Think back to that natural gas leak in California.

I didn’t predict the disaster. I figured out which publicly traded company was exposed and found unusual trading activity that suggested an opportunity.

With CoreWeave and Oracle, the setup was different. I was looking at financial risks building underneath two popular AI stocks.

But the principle is the same: Don’t just watch the headlines. Follow the money.

That’s the approach behind my premium trading service. We watch for unusual trading activity – large trades that stand out from the normal buying and selling.

Not every big trade means something, and not every trade works out. But when somebody puts serious money behind an unusual position, I want to know about it.

Then we look for an opportunity where we can define our risk before putting money on the line.

That’s the approach I share in my free $10K to $100K Challenge presentation, which went up just a couple of days ago.

In it, we go over how I look for unusual trading activity, evaluate opportunities, and manage risk as we pursue the possibility of turning $10,000 into $100,000 in 12 months.

It’s an ambitious goal, and I won’t pretend otherwise. But you can learn the process.

But you can learn the process. And you can learn to look beyond the stock price for signs of what might happen next.

Go here to learn more about my strategy.

P.S. Jonathan and I use different methods to find opportunities in the market, but we agree that having a disciplined process matters. His August warnings about CoreWeave and Oracle are a good reminder that even exciting investment themes can carry serious risks. And his experience on the trading floor has taught him to watch for unusual activity that other investors might miss. If you’d like to see how Jonathan approaches the market, I encourage you to watch his free $10K to $100K Challenge presentation.

The post The AI Selloff Is Sending Investors a Warning, and Here’s Where to Look appeared first on InvestorPlace.

In 1999, the legendary value investor Bill Miller walked out of a meeting with executives from Amazon.com Inc. (AMZN).

Miller was convinced he’d found the most capital-efficient retailer ever created. In a Barron’s article, he detailed how Amazon was potentially the future of shopping and concluded that the “payoff for being right is high.”

His Legg Mason Capital Management fund bought millions of shares for an average cost of $1.50, adjusted for splits.

Miller was right. Eventually.

Today, Amazon is worth over $250 a share. The company towers over the retail landscape, dominating areas like books, smart home devices, and household goods. It’s now hard to remember life without same-day shipping.

But Miller lost a lot of money on Amazon at first.

You see, the fund manager began buying shares right as the dot-com bubble was bursting. Amazon’s stock would fall to $0.30, and Miller’s position was in the red for years.

That’s why I warned you about buying quantum computing stocks last month. Even though shares of these companies will likely do fantastically over the next decade, their risky nature means you could lose a lot of money at first. Much like investing in Amazon in the 1990s, you need a 10-plus year horizon to buy quantum stocks today, if you plan on using a buy-and-hold strategy.

However, our resident trading expert, Jonathan Rose, is more interested in generating returns today.

In fact, he’s so confident in his trading system that he’s calling his latest free presentation the $10K to $100K Challenge. In it, he outlines how his system spots the tiny clues that professional traders leave behind, opening the door to more immediate returns… the sort that can turn $10,000 into $100,000 in just a year.

He will also make available three of his top trades after that presentation. And today, I’ve been given permission to reveal one of his three picks.

To learn more about the other two, click here to watch the replay of Jonathan’s $10K to $100K Challenge.

A Quantum Leap Forward

Quantum computers have long been the “holy grail” of computing. That’s because the subatomic particles described by quantum physics are not limited by the binary “0s” and “1s” of ordinary computers. Instead, quantum “bits” can live between “0” and “1” as well.

The possibilities here are vast. Quantum computers will be able to perform enormous numbers of calculations at the same time. They will also be able to break modern encryption, develop new drugs, and maybe even train AI models. I expect the industry to be worth trillions in a decade or so, and I highlighted three top contenders last month with the technology that could get us there.

However, those seeking shorter-term gains might want to consider D-Wave Quantum Inc. (QBTS), one of Jonathan’s recommendations in his $10K to $100K Challenge.

Let’s start with some background on the company…

A Business and a Bet

D-Wave began in 1999 as a spinout from the University of British Columbia in Vancouver. For the first 10 years, it was a physics project with not much of a business model. But in 2011, D-Wave became the first company to ever sell a quantum machine when Lockheed Martin Corp. (LMT) bought one for about $10 million.

D-Wave was so early because it used a relatively limited version of quantum computing known as annealing. It’s a narrow approach that can only do one thing: Find the lowest point.

There’s no encryption breaking. No drug molecule simulations. No Shor’s algorithm.

Instead, D-Wave’s computers can only do optimization problems, like finding the lowest point in a mountain range, or the shortest trip a postal worker can make. That makes D-Wave’s “computers” more like a wind tunnel – a useful tool, but good at only one task. That is not enough to turn D-Wave into a $100 billion company.

That’s almost certainly why D-Wave bought Quantum Circuits earlier this year for $800 million. That Yale University spinout is working on a more general-purpose quantum computer that now puts D-Wave on a better track to reaching the “holy grail” of computing.

The Bet Worth Taking

The obvious problem with D-Wave today is the same one that Bill Miller faced in 1999 with Amazon:

You know a new technology is a game changer, but it’s not clear when to get in.

Jonathan Rose’s system looks to solve this. By tracking “smart money” activity, his system detects when and where Wall Street is placing their bets and picks out which names are most likely to break out. It’s helped him navigate markets for over two decades, and he continues to use it to find the most promising bets for further investigation.

The system is now flagging D-Wave as a potential breakout stock.

Since the end of July, traders have been making major bullish bets on D-Wave. Open interest on bullish positions has more than doubled since July, while bearish positions are only up 67%. This has happened even as D-Wave’s stock was going down.

The positive bets are particularly noticeable for contracts expiring in late Q1 2027. The heavy bullish trading activity centered around that period suggests that Wall Street is convinced D-Wave will make a major upward move by March of next year.

So, why might Wall Street’s “smart money” buy a quantum stock that’s down 57% since June?

It certainly has nothing to do with quantum technology itself. A useful general-purpose quantum computer won’t appear until at least 2030, and I don’t expect D-Wave to get there first. Alphabet Inc. (GOOGL) is much further along.

But the interesting thing about tactical trading in D-Wave is that it does not depend on quantum computing at all. Instead, it’s all about certain announcements happening as scheduled.

The Bear Case is Breaking

For nine years D-Wave’s short sellers have had one argument: Revenue never comes.

Quarter after quarter, D-Wave has announced disappointing sales numbers that barely dented its nine-figure cost base. In fact, the company has now missed revenue estimates in 14 of its past 17 quarters. It’s why short interest has risen from around 10% of floated shares in 2024 to 16% in 2025, and almost 20% today.

The sharks are circling because there’s so much blood in the water.

The tide is finally turning. For the first time in the company’s history, D-Wave now has a meaningful amount of contracted revenues on its balance sheet. The company signed a $20 million contract with Florida Atlantic University in January, which helped bring its overall backlog to $40.7 million, up 688% in a year. It expects to convert more than half of that backlog into revenues by year-end.

That means fourth-quarter revenue estimates of $32 million are no longer just built on hope. The company finally has contracts it can convert into revenue, and its year-end numbers published in February should show a historic “surge” in sales.

That would suddenly change the optics for QBTS. The quantum computing firm would transform from a near-zero revenue company to one that looks like a hypergrowth firm. That alone could be enough to lure in new money that chases out the short sellers.

Rushing for the Exits

Chasing out the shorts deserves a special mention. D-Wave is currently a highly shorted stock, and these bearish traders are now sitting on large paper profits that can evaporate in an instant. If the stock suddenly shoots up (whether from rising revenues or swarm buying), every dollar of gains for long holders is a dollar of loss for these bears.

And here’s the thing: When short sellers close out, they need to buy the stock, not sell. That creates an upward pull on share prices, causing even more short sellers to close out, and so on.

This vicious cycle of buying is called a short squeeze, and it is every short seller’s worst nightmare.

So, how likely is it to happen to D-Wave?

As Eric Fry explains in a recent Fry’s Investment Report update (subscription required), the risk of a short squeeze is summed up by one measure known as “days to cover”:

Professional short sellers gauge crowding with a simple yardstick called “days to cover.” It answers one question: If every short seller tried to buy back their shares at once, how many days of normal trading would it take to get the job done?

Today, D-Wave’s 71 million shorted shares would take 4.5 days to unload, roughly the same amount of time it would take GameStop Corp.’s (GME) short sellers to exit. And because D-Wave is even more volatile than GameStop (since it is a smaller firm), the risk of a squeeze is even higher.

We saw this firsthand in September 2025, when QBTS surged from $15 to almost $40 within a month. Quantum stocks saw renewed investor interest, and the initial rise was compounded as short sellers cut their positions.

What should have been a minor rally in QBTS turned into a bonanza for the longs.

D-Wave’s “days to cover” number is now even higher than in 2025. And so, if the stock begins to rally, we could easily see shares going into the mid-$20 range on short covering.

Turning a Good Idea into a Great Trade

Now, I must note that a tactical position in QBTS is very risky. The company is still losing money, and the expected Q4 sales boost won’t come close to helping D-Wave break even.

Analysts expect net losses to hit $102 million this year, driven by heavy spending on research, sales, and stock-based compensation. Next year looks even worse as R&D spending ramps up.

That’s why investors need a way to tilt the odds further in their favor.

To do this, Jonathan uses a particular type of trade that will benefit if QBTS moves higher through March 2027. The maximum amount you can lose is the money you put in – much like what happens when a stock goes to zero. For a speculative company like D-Wave, this is always a real possibility.

But if QBTS doubles to $25, Jonathan’s strategy would net you a 6X increase by March, rather than the 2X rise had you just bought the stock outright.

Now, if this sounds too good to be true, I’d like you to watch Jonathan’s presentation. In it, he explains exactly how he sets his trades up for such lopsided gains, how to know when it’s time to cut losses, and how you too can use his system to identify potential winners and make the right kinds of trades.

We know D-Wave is an extremely risky stock in the short term. So, we might as well set up any wager to magnify gains if they materialize.

Click here to watch Jonathan’s presentation.

Until next week,

Thomas Yeung, CFA

Market Analyst, InvestorPlace

Thomas Yeung is a market analyst and portfolio manager of the Omnia Portfolio, the highest-tier subscription at InvestorPlace. He is the former editor of Tom Yeung’s Profit & Protection, a free e-letter about investing to profit in good times and protecting gains during the bad.

The post One Short-Term Stock to Buy for the Next Tech Revolution appeared first on InvestorPlace.

One October, in the late 1880s, just before 1 p.m., two Western Union linemen climbed a pole in lower Manhattan to cut down dead electrical wires. Only one returned alive.

Atop the 50-foot-high pole, crowded with electric wires, a nearby fireman caught a terrifying glimpse of the grisly scene.

One of the men, John Feeks, fell from the pole, struck a crossarm, and came into contact with an electric wire.

At that moment, “The current was completed,” the Ann Arbor Register reported.

Feeks’s body stiffened. His leg remained hooked over the crossbar.

“There was no movement.”

His coworker scrambled down and fled. Below, people witnessed a scene Deputy Coroner Jenkins described as the most ghastly he had ever seen. Even afterward, Jenkins could not say whether the current had killed Feeks immediately: “The shock may or may not have killed him instantly.”

The horror soon became public fury, and a full-blown electric wire panic. Building owners cut wires above their rooftops. Newspapers demanded accountability. The next day, Mayor Hugh Grant ordered unsafe wires removed.

New York had already passed legislation requiring wires to go underground. Feeks’s death gave that longstanding fight a terrible urgency.

The Backlash Didn’t Stop Electrification

Put yourself in an investor’s shoes.

A technology that promised to transform everyday life had become a source of public terror. As a result, authorities ordered its infrastructure torn down.

Would you have bet on the future of electricity?

Two years later, a traveling lineman named Henry Miller organized a convention in St. Louis that founded what became the International Brotherhood of Electrical Workers. Today, electrical power-line installers and repairers earn a median $95,320 a year, or nearly twice the median for all occupations.

The lesson I draw is that a technology’s dangers can make the work of building and maintaining it more valuable.

And that brings me to AI.

When investors see backlash, they tend to ask how much growth it could destroy. I think there’s another question worth asking:

How do we solve the problems standing in our way?

That’s the question I’d bring to the AI debate in 2026. Because investors who see only the panic may be putting fear of the unknown ahead of the opportunity.

$130 Billion in Projects Were Blocked or Delayed

Let’s give the panic its due first – because it’s real, and now it’s measurable.

Organized opposition delayed or blocked an estimated $130 billion worth of U.S. data-center projects in the first quarter of 2026 alone. New York enacted the nation’s first statewide moratorium on new hyperscale facilities over the summer. And AWS chief Matt Garman says more than 100 local moratoriums are now under consideration across the country, as communities push back on electricity prices, water use, construction, and secrecy around new projects.

The industry is already reaching for the old playbook. 

Amazon (AMZN) just committed more than $1 billion to its host communities in a move we’d call the 2026 version of burying the wires.

The electric industry didn’t win its fight by dismissing public fear but by spending money to address it. 

The data-center industry just started doing the same thing.

The Backlash Is Rerouting AI Spending, Not Ending It

Meanwhile, the demand behind this buildout just got locked in.

Anthropic’s leaked initial public offering (IPO) prospectus reportedly shows roughly $518 billion in compute and infrastructure commitments. About 80% of that is noncancelable or payable regardless of usage, with obligations stretching into the 2030s. And OpenAI’s annualized revenue run rate is approaching $70 billion, up more than 70% since the start of the third quarter.

And Wall Street keeps lining up behind the buildout: 

• SpaceX (SPCX) is reportedly seeking $40 billion in debt to buy Nvidia chips. 
• Lenders including Apollo and Blackstone are assembling a $50 billion-plus package to finance OpenAI’s custom silicon. 
• CoreWeave (CRWV) is courting insurance-company capital. 

Even this month’s rate-driven selloff in the most leveraged AI names hasn’t touched those commitments.

The Data Center Stocks Benefiting From the Bottlenecks

So, the backlash isn’t stopping AI dollars. Rather, it’s rerouting them toward the companies that build, wire, and power data centers on-site.

Follow the paychecks and you’ll see it. Experienced electricians now command north of $100,000. Postings for welders and pipefitters are up 164% year over year. Welders can graduate high school and earn $65,000 to $75,000 in short order, with almost unlimited overtime.

Unlike the internet boom, which mostly rewarded advanced degrees, this is a blue-collar resurgence. And it shows up in the order books.

EMCOR Group Inc. (EME) ended June with a record $17.1 billion in remaining performance obligations, up 44% year over year. Comfort Systems USA Inc. (FIX) posted a record $14.1 billion backlog, up 73%. Quanta Services Inc. (PWR) is sitting on $53.4 billion.

On the power side, Bloom Energy Corp. (BE) topped $1 billion in quarterly revenue for the first time, up 166%. Caterpillar Inc. (CAT), whose generators are a go-to for on-site power, is one of our favorite ways to play this. And Anthropic just signed an $11.6 billion, seven-year compute deal with Akamai Technologies Inc. (AKAM) to tap its distributed cloud network.

Could Orbital Data Centers Bypass Some of Earth’s Constraints?

Now take that logic all the way.

If land, water, and angry neighbors are the constraint, what happens when you build somewhere with no neighbors at all?

A few weeks ago, SpaceX (SPCX) sent Starship into orbit for the first time. Elon Musk says the company’s first AI compute satellites, powered by Nvidia Corp. (NVDA) chips, will launch in late 2027 and hit “significant scale” in 2028. 

Then Alphabet Inc.’s (GOOGL) Google sent its own AI chips into orbit shortly after – alongside two startups testing whether power can be beamed between satellites.

It’s early, and it’s expensive. Barclays estimates orbital compute costs roughly three times as much as building on the ground. For the next few years, the boom here on Earth keeps rolling.

But I keep coming back to one thing in particular…

In 1889, Thomas Edison and George Westinghouse dominated the headlines, which locked in their war of the currents. The steadier fortunes went to the builders who strung the wire, dug the conduits, and supplied the equipment that electrified the country.

The same thing is happening today. Only the headlines are about moratoriums and chatbots. Wherever new infrastructure goes, a class of builders and suppliers follows. They rarely get the magazine covers, but they’re usually where the money is made.

Orbital data centers won’t be any different. Everyone is watching SpaceX. Yet, far fewer are watching the companies that will build, launch, power, and connect the compute Musk wants to put in space.

That supply chain is what I call “XPANSE.” And I think it could be one of the most asymmetric setups in the entire AI trade.

I’ve put together a full briefing on it, including the companies I believe are best positioned to profit as this buildout leaves the ground.

Click here to see my full XPANSE presentation.

The post Data Center Backlash Isn’t Killing AI Spending. It’s Changing Where the Money Goes. appeared first on InvestorPlace.

A motorcycle helmet might not be as safe as you think.

Now, obviously, helmets can and do save the lives of riders who get into serious accidents. And they should be worn.

But, although it sounds counterintuitive, wearing a helmet can also contribute directly to a fatal accident that a helmetless rider might have avoided. For reckless riders, the protective measure can turn into a false sense of invincibility.

After California passed its 1992 helmet law, motorcycle fatalities per 10,000 registered motorcycles fell for a few years, then leveled off and rose.

From 1997 to 2007, the annual number of motorcycle fatalities per registered bike nearly doubled… and returned to where it was before the helmet law was passed. It was as if the law never changed.

The data shows a simple human truth: We tend to convert potential safety benefits into performance benefits.

Helmeted riders may feel more invincible, encouraging risky habits such as speeding or “splitting traffic.” These behaviors, combined with helmets’ sensory impairments, could explain why motorcycle deaths returned to pre-helmet levels.

There is a similar false sense of security on Wall Street.

U.S. stocks have delivered consistent, world-beating results for nearly two decades. That success has made American stocks feel like the safer choice – while foreign stocks, by comparison, can seem riskier.

Just as helmets can make reckless riders feel invincible, years of strong U.S. stock returns can make investors feel safer than they are. They may stick with what has worked, overlooking foreign markets that could offer better value and help diversify their portfolios.

So, in today’s Smart Money, I’ll explain why this overconfidence can lead investors to favor U.S. stocks even when foreign markets offer compelling alternatives.

Then, I’ll walk you through the hidden risks of sticking with the status quo, and point you toward several overseas opportunities I’m backing that most U.S. investors overlook.

The Real Reason U.S. Stocks Soared

Before assuming U.S. stocks are inherently better investments, we need to first understand what has driven their outperformance – and whether that can continue.

From the lows of 2009, the S&P 500 has delivered a total return of roughly 1,340%, nearly triple the MSCI EAFE Index’s 468% return over the same period. The EAFE Index tracks developed markets in Europe, Australasia, and the Far East.

From a self-congratulatory perspective, we might assume that American technological prowess and economic dynamism have been powering the massive outperformance of U.S. stocks. But upon closer examination, we find a much more pedestrian explanation:

Multiple expansion.

That’s the term Wall Street analysts use to describe the boost a stock receives when its valuation increases from low levels to higher levels. In other words, a big chunk of the S&P 500’s gains came not from stronger businesses, but from investors simply paying more for them.

Currently, the S&P 500 trades for about 26 times earnings, compared with under 18 for the EAFE. Multiple expansion can’t continue forever. And when valuations stretch this far, even good news can struggle to push prices higher, while bad news can send them sharply lower.

Plus, market leadership never lasts forever.

The chart below shows the difference between the EAFE Index’s rolling five-year net returns and the S&P 500’s returns.

When the black line is in the green space, the EAFE has been outperforming the S&P 500 over the preceding five years. When it’s in the red, EAFE has been underperforming.

The first major period of outperformance ran from March 1986 to March 1991. In 1986 alone, the EAFE Index returned nearly 67%, more than triple the S&P 500’s 18.7% gain.

The second ran from November 2003 to February 2011. In November 2006, the EAFE had returned 13.79% per year over the prior five years, while the S&P 500 had returned just 6.09% per year.

The black line’s slight upturn on the right-hand side reflects that the EAFE and S&P have delivered nearly identical returns over the last two years.

Now, I want to be clear: This recent trend only suggests, not proves, that U.S. momentum may be fading relative to foreign stocks. Still, as we’ve seen, history shows that a shift is possible.

Yesterday’s winners aren’t guaranteed to lead tomorrow – which is why investors must strengthen their portfolios today. Here’s how…

Familiar Isn’t Safe

No matter what happens next, we American investors should never remain “overweight” in U.S. stocks and bonds, simply because they are familiar. We must remember that, as investors, the world truly is our oyster.

In times like these – when the U.S. markets are featuring more uncertainty than average and U.S. stock valuations are much higher than average – select foreign markets deserve a closer look.

In other words, if a new cycle of outperformance by foreign stock markets is underway, we should try to maximize that opportunity by diversifying some of our capital into select foreign investments.

That doesn’t mean U.S. stocks are a bad investment. Far from it. But holding them isn’t the risk. Assuming they’ll always lead is. I’m not predicting U.S. stocks will crash or that foreign stocks will soar. I’m saying the safest assumption is that leadership changes, and that diversification protects you either way.

That’s why, at Fry’s Investment Report, we’ve already begun cautiously diversifying into select foreign markets. One of our recommendations is a South American ETF that has soared 81% since we added it last year, while the S&P 500 gained only 48% over the same timeframe.

Another recommendation is an Asian ETF that has been benefiting from rising demand for robotics and other AI technologies. That one has advanced a solid 51% since joining the portfolio, compared to a gain of only 34% for the S&P 500.

I believe both still have plenty of runway ahead.

It’s understandable that a U.S.-heavy portfolio feels safe after years of strong returns. But that’s also what makes it dangerous, like the helmeted rider who starts splitting traffic.

My advice: Wear your investing helmet; don’t abandon U.S. stocks. But, at the same time, don’t be afraid to change lanes.

To access my latest research and recommendations on foreign stocks, click here to join me at Fry’s Investment Report.

Regards

Eric Fry

P.S. If you had $10,000 to invest right now, where would you put it? In the debut episode of The Investor Place podcast, I – along with my colleagues Louis Navellier and Jonathan Rose – share where to find the next big opportunities in the AI trade and name specific stocks to watch. I also share my thoughts on the AI buildout as a whole, as well as other overlooked ways to hedge your portfolio today. Click here to watch now.

The post Why Playing It “Safe” With U.S. Stocks Could Backfire appeared first on InvestorPlace.

It was one of the most consequential product demonstrations in history – and it helped make the inventor rich while changing the way we live.

At the New York Crystal Palace in 1854, an assistant stood high above the floor holding an axe beside the only rope keeping Elisha Otis from plunging to the ground.

Below them, a crowd waited.

Otis was standing on an open elevator platform suspended over the exhibition hall.

Then he gave the order, the axe fell, and the platform dropped.

But it fell only a few inches.

A safety mechanism Otis had invented caught the platform and held it securely in place.

To be clear, Otis did not invent the elevator. Hoists had been carrying freight and people between floors for centuries.

But he solved the problem that prevented people from trusting them.

In the mid-1800s, elevators relied on ropes that could break, sending their platforms and any passengers plunging to the ground.

Otis devised a spring-loaded safety brake that would engage if the supporting rope failed.

This simple demonstration changed Otis’ fortunes by boosting demand for this new device.

Otis didn’t invent elevators or skyscrapers, but the proliferation of safe elevators allowed plans for “skyscrapers” to flourish.

Credit: zxvisual

A new kind of city was now possible.

And it wasn’t just the fear of an accident that Otis’ invention solved. Practically, before safe passenger elevators, the upper floors of a building were often the least desirable. After all, every additional story meant another flight of stairs.

Otis’ mechanism helped remove that limitation.

Architects could design taller buildings. Businesses and residents could occupy their upper floors. Eventually, the least desirable space in a building became the most prestigious.

That’s the power of the right invention at the right time.

The Companies that Make Grand Visions Possible

History offers plenty of stories that follow this pattern.

The visionary inventor or company announces an ambitious new product or project. The founder appears on magazine covers and (nowadays) in every podcast. His or her name appears in the headlines of every financial media outlet.

But as great as the vision is, someone must solve the practical problems standing in its way.

Someone must supply the specialized materials… manufacture the critical components… build the infrastructure… or remove the bottleneck preventing the technology from reaching its full potential.

The companies that solve these problems may never become household names. But for investors, they can create extraordinary opportunities.

That is precisely the kind of opportunity our technology expert Luke Lango has been focusing on.

In his Innovation Investor service, Luke likes to say that companies are creating wealth at exorbitant rates. He focuses on investing in innovation, the best investment strategy in the market during times of great technological change.

In August, Luke recommended ASE Technology Holding Co., LTD (ASX) to his Innovation Investor readers as a prime example of a company providing a critical component of the AI megatrend.

Before a semiconductor chip can be sold, it must be packaged, physically protected and wired up so it can connect to a circuit board and tested. ASE is the world’s largest company specializing in that step.

As a result, it has become critical for the advanced packaging techniques needed to build today’s AI chips, stacking multiple chips together and connecting them to high-bandwidth memory in incredibly tight, precise configurations. Here is Luke explaining why ASX is positioned to benefit.

Taiwan Semiconductor (TSMC), the world’s leading chip manufacturer and the company that etches most of the world’s advanced AI chips, does not have enough of its own advanced packaging capacity to keep up with demand, so it outsources a meaningful chunk of that overflow work to ASE.

ASE is not just riding AI demand; it is benefiting from a genuine capacity bottleneck in a step of the supply chain that cannot be skipped. That scarcity has given ASE real pricing power: reports indicate the company has raised advanced packaging prices more than 20% this year alone, driven by relentless demand from AI accelerator customers.

That is what Luke looks for – not simply a company participating in a fast-growing trend, but one controlling a critical step that cannot be skipped.

In ASE’s case, that step is advanced chip packaging.

Below is the stock’s performance since Luke’s recommendation.

As you can see, the stock has been hit by the same downturn affecting all AI stocks recently.

But here is why Luke is still optimistic:

Management raised its 2026 outlook for its advanced packaging division, which it calls “LEAP,” to more than $3.5 billion in revenue, and it is backing that outlook with capital: 2026 capital spending guidance was raised to $8.5 billion, with additional increases possible, specifically to expand capacity for demand management expects well into 2029 and 2030.

This translates into a projected 25% compounded annual revenue growth through 2030, with meaningful room for EBITDA margin expansion from pricing power, putting compounded EBITDA growth at more than 35%. 

Now, Luke has identified three more potential bottlenecks – this time involving Elon Musk’s most ambitious undertaking yet.

The Companies Elon Musk May Soon Need

Luke believes Musk is preparing to bring together Tesla, SpaceX, xAI, X, and the other pieces of his technological empire around one sweeping vision.

Luke calls it “XPANSE.”

It could include orbital AI data centers… an enormous semiconductor complex… and armies of Optimus robots.

But just as skyscrapers could not reach their potential until Otis made elevators safe, Musk’s vision cannot become reality until someone solves the practical problems standing in its way.

Luke has identified three companies that could help.

One specializes in the complex solar arrays Musk could need to power data centers in orbit.

Another produces highly specialized equipment that could become essential to Musk’s semiconductor complex.

And the third controls an important American source of the rare earth materials and powerful magnets required for robots, satellites, and advanced machinery.

These companies will likely never become as famous as Tesla or SpaceX. But a major contract from Musk could completely transform any one of them.

That’s why Luke recently recorded a special presentation revealing Musk’s larger plan – and the three little-known companies he believes are best positioned to help make it possible.

Click here to watch Luke’s presentation and discover all three potential XPANSE suppliers.

Elisha Otis didn’t build the skyscraper.

He removed the obstacle that allowed it to rise.

Luke believes these three companies could play a similar role in Elon Musk’s next technological empire.

Enjoy your weekend,

Luis Hernandez

Editor in Chief, InvestorPlace

The post Elon Gets the Headlines; These Stocks Could Get the Gains appeared first on InvestorPlace.

In August, I flagged two AI market darlings: CoreWeave and Oracle. Since then, both stocks have taken a hit.

Anyone following Masters in Trading LIVE has known about this story for weeks. Today, I want to show you why I’m still betting against the broader market sentiment around these stocks — and I want to give you the tools to spot stories just like this before the crowd catches on.

I recently showed how I use options to pursue outsized gains in my free $10K to $100K Challenge presentation. If you haven’t watched it yet, I encourage you to check it out.

Now, read on to see what I spotted early, why it matters, and what you can learn from it.

In October 2015, a natural gas well near Los Angeles started leaking methane.

And I don’t mean a little leak. This thing was a catastrophe.

The leak came from an underground storage facility tucked into the mountains just above LA’s sprawling San Fernando Valley. Soon, a rotten-egg stench was drifting through nearby neighborhoods.

Residents reported headaches, nausea, and nosebleeds. Thousands of families fled to hotels and temporary housing, with no idea when they could return. Two local schools had to be relocated.

The leak wouldn’t be stopped for 111 days.

But something about the coverage bothered me. Every article talked about Southern California Gas Co.

OK. But I had an additional question: Who owned SoCalGas?

Turns out the parent company was Sempra (SRE), a publicly traded utility.

I pulled up Sempra on my screener and found something that stopped me cold. Somebody had made an unusually large bearish trade against the company.

I had two pieces of information: a major environmental disaster involving a Sempra subsidiary… and a big bearish trade in the parent company’s stock.

I didn’t know who placed that trade or what they knew. But I’d spent years trading on the floors of the Chicago exchanges, where I learned to pay attention when large trades show up in unusual places.

Somebody was putting real money behind a bet that Sempra was going lower.

So I shared a bearish trade of my own with my followers. With it, we risked $200 for the opportunity to make $4,800.

A few days later, California declared a state of emergency, and Sempra’s stock plunged. One of my followers later told me he’d made $9,600 after risking $400.

Here’s another part I love.

I found a reporter covering the leak who hadn’t mentioned Sempra, so I reached out and pointed out that SoCalGas had a publicly traded parent company. She wrote back that she was working on a follow-up.

That’s what I mean when I talk about following the money.

While everybody was watching the gas leak, I was watching the company behind it – and what traders were doing with its stock.

This August, I spotted something similar in a very different business: artificial intelligence.

Two AI Stocks I Didn’t Want to Own

On August 17, I was hosting my daily Masters in Trading LIVE show. We were talking about retail earnings and consumer health.

Then I changed the subject to two AI companies that had me worried: CoreWeave Inc. (CRWV) and Oracle Corp. (ORCL).

Now, I’m still very bullish on AI. I love what Nvidia Corp. (NVDA) is doing. I think artificial intelligence will create enormous opportunities for years to come.

But that doesn’t make every AI company a good investment.

CoreWeave and Oracle were borrowing enormous amounts of money to build AI infrastructure.

CoreWeave rents computing power to AI companies. That means buying expensive chips, building data centers, and spending a fortune before all that equipment generates revenue.

Oracle is making its own enormous investments in AI data centers, with a substantial portion of its future business tied to OpenAI.

Then there’s what’s called “circular financing.”

Nvidia sells chips to CoreWeave. Nvidia also owns a stake in CoreWeave. AI companies sign massive agreements to rent computing capacity. The companies providing that capacity borrow money to buy more equipment.

Everybody announces another billion-dollar deal, and investors get excited.

But I have a question: Where is all this money actually coming from?

When companies borrow billions and funnel money among the same group of businesses, those impressive deals can conceal a great deal of financial risk.

That’s why I called my August 17 show the AI House of Cards.

I told viewers that if the market turned, CoreWeave and Oracle would be among the first companies to get hit. I didn’t want to be long either stock. In fact, I suggested CoreWeave shareholders consider taking their profits.

CoreWeave was trading around $106 when I issued my warning.

Things Get Interesting

Now, I need you guys to stay awake for a minute. I’m going to talk about bonds.

I know, I know. Everybody’s favorite subject.

But this is important.

Most investors watching CoreWeave were looking at the stock price, Nvidia, and all those enormous AI deals. I was looking at what it cost CoreWeave to borrow money.

CoreWeave had issued bonds paying 9.6% interest, but those bonds were now trading at prices that pushed the yield to around 15%. That’s a massive jump.

That means investors were demanding much more compensation to take on CoreWeave’s risk. Somebody was getting nervous. And the warning appeared in the debt market before it became obvious in the stock price.

Oracle was showing warning signs, too. The cost of insuring its debt against default had risen sharply.

When you’re borrowing billions to build data centers, the cost of money matters. And when lenders get nervous, stockholders had better pay attention.

What Happened After My Warning

On October 15, I revisited CoreWeave and Oracle during Masters in Trading LIVE.

CoreWeave had fallen from approximately $106 on August 17 to around $61. That’s a decline of roughly 42% in less than two months.

Oracle had taken a beating, too. Other AI infrastructure names were under pressure.

The immediate trigger wasn’t necessarily a new discovery about AI. Hotter-than-expected inflation raised concerns about interest rates and borrowing costs.

And companies carrying enormous financial obligations were particularly vulnerable. That’s what worried me in August.

Look, CoreWeave has real customers and an enormous backlog of contracted business. Some investors see a tremendous opportunity after this decline.

Fine.

But there’s a difference between having billions in business lined up and having the financial strength to deliver it profitably. And when you borrow heavily to fund growth, you don’t have much room for things to go wrong.

Here’s another thing I told viewers on Thursday. I wouldn’t make a new bearish trade on CoreWeave at $61.

The stock has already been punished. Could it go lower? Absolutely. But a good warning in August doesn’t automatically make it a good bearish trade in October.

Being right about the problem doesn’t automatically make every price a good place to bet against it. The trade has to make sense too.

That’s why I always want to know my risk before entering a trade.

What the Big Money Is Telling Us

Think back to that natural gas leak in California.

I didn’t predict the disaster. I figured out which publicly traded company was exposed and found unusual trading activity that suggested an opportunity.

With CoreWeave and Oracle, the setup was different. I was looking at financial risks building underneath two popular AI stocks.

But the principle is the same: Don’t just watch the headlines. Follow the money.

That’s the approach behind my premium trading service. We watch for unusual trading activity – large trades that stand out from the normal buying and selling.

Not every big trade means something, and not every trade works out. But when somebody puts serious money behind an unusual position, I want to know about it.

Then we look for an opportunity where we can define our risk before putting money on the line.

That’s the approach I share in my free $10K to $100K Challenge presentation, which went up just a couple of days ago.

In it, we go over how I look for unusual trading activity, evaluate opportunities, and manage risk as we pursue the possibility of turning $10,000 into $100,000 in 12 months.

It’s an ambitious goal, and I won’t pretend otherwise. But you can learn the process.

But you can learn the process. And you can learn to look beyond the stock price for signs of what might happen next.

Go here to learn more about my strategy.

Remember, the creative trader wins.

Jonathan Rose,

Founder, Masters in Trading

The post The AI Selloff Is Sending Investors a Warning, and Here’s Where to Look appeared first on InvestorPlace.

Which helped lead him to warn about CoreWeave and Oracle back in August, before the stocks took a beating.

That’s what I find so fascinating about Jonathan’s approach of looking beyond the story everyone is talking about, following the money and asking whether a trade makes sense at the right price.

In his free $10K to $100K Challenge presentation, Jonathan explains how he investigates unusual trading activity and defines his risk before putting money on the line. There’s still time to watch his presentation. Click here to learn how his approach works.

But first, here’s Jonathan with the warning signs he spotted and why being right about a stock doesn’t automatically make it a good trade today.

*************************

Hey, guys.

In October 2015, a natural gas well near Los Angeles started leaking methane.

And I don’t mean a little leak. This thing was a catastrophe.

The leak came from an underground storage facility tucked into the mountains just above LA’s sprawling San Fernando Valley. Soon, a rotten-egg stench was drifting through nearby neighborhoods.

Residents reported headaches, nausea, and nosebleeds. Thousands of families fled to hotels and temporary housing, with no idea when they could return. Two local schools had to be relocated.

The leak wouldn’t be stopped for 111 days.

But something about the coverage bothered me. Every article talked about Southern California Gas Co.

OK. But I had an additional question: Who owned SoCalGas?

Turns out the parent company was Sempra (SRE), a publicly traded utility.

I pulled up Sempra on my screener and found something that stopped me cold. Somebody had made an unusually large bearish trade against the company.

I had two pieces of information: a major environmental disaster involving a Sempra subsidiary… and a big bearish trade in the parent company’s stock.

I didn’t know who placed that trade or what they knew. But I’d spent years trading on the floors of the Chicago exchanges, where I learned to pay attention when large trades show up in unusual places.

Somebody was putting real money behind a bet that Sempra was going lower.

So I shared a bearish trade of my own with my followers. With it, we risked $200 for the opportunity to make $4,800.

A few days later, California declared a state of emergency, and Sempra’s stock plunged. One of my followers later told me he’d made $9,600 after risking $400.

Here’s another part I love.

I found a reporter covering the leak who hadn’t mentioned Sempra, so I reached out and pointed out that SoCalGas had a publicly traded parent company. She wrote back that she was working on a follow-up.

That’s what I mean when I talk about following the money.

While everybody was watching the gas leak, I was watching the company behind it – and what traders were doing with its stock.

This August, I spotted something similar in a very different business: artificial intelligence.

Two AI Stocks I Didn’t Want to Own

On August 17, I was hosting my daily Masters in Trading LIVE show. We were talking about retail earnings and consumer health.

Then I changed the subject to two AI companies that had me worried: CoreWeave Inc. (CRWV) and Oracle Corp. (ORCL).

Now, I’m still very bullish on AI. I love what Nvidia Corp. (NVDA) is doing. I think artificial intelligence will create enormous opportunities for years to come.

But that doesn’t make every AI company a good investment.

CoreWeave and Oracle were borrowing enormous amounts of money to build AI infrastructure.

CoreWeave rents computing power to AI companies. That means buying expensive chips, building data centers, and spending a fortune before all that equipment generates revenue.

Oracle is making its own enormous investments in AI data centers, with a substantial portion of its future business tied to OpenAI.

Then there’s what’s called “circular financing.”

Nvidia sells chips to CoreWeave. Nvidia also owns a stake in CoreWeave. AI companies sign massive agreements to rent computing capacity. The companies providing that capacity borrow money to buy more equipment.

Everybody announces another billion-dollar deal, and investors get excited.

But I have a question: Where is all this money actually coming from?

When companies borrow billions and funnel money among the same group of businesses, those impressive deals can conceal a great deal of financial risk.

That’s why I called my August 17 show the AI House of Cards.

I told viewers that if the market turned, CoreWeave and Oracle would be among the first companies to get hit. I didn’t want to be long either stock. In fact, I suggested CoreWeave shareholders consider taking their profits.

CoreWeave was trading around $106 when I issued my warning.

Things Get Interesting

Now, I need you guys to stay awake for a minute. I’m going to talk about bonds.

I know, I know. Everybody’s favorite subject.

But this is important.

Most investors watching CoreWeave were looking at the stock price, Nvidia, and all those enormous AI deals. I was looking at what it cost CoreWeave to borrow money.

CoreWeave had issued bonds paying 9.6% interest, but those bonds were now trading at prices that pushed the yield to around 15%. That’s a massive jump.

That means investors were demanding much more compensation to take on CoreWeave’s risk. Somebody was getting nervous. And the warning appeared in the debt market before it became obvious in the stock price.

Oracle was showing warning signs, too. The cost of insuring its debt against default had risen sharply.

When you’re borrowing billions to build data centers, the cost of money matters. And when lenders get nervous, stockholders had better pay attention.

What Happened After My Warning

On October 15, I revisited CoreWeave and Oracle during Masters in Trading LIVE.

CoreWeave had fallen from approximately $106 on August 17 to around $61. That’s a decline of roughly 42% in less than two months.

Oracle had taken a beating, too. Other AI infrastructure names were under pressure.

The immediate trigger wasn’t necessarily a new discovery about AI. Hotter-than-expected inflation raised concerns about interest rates and borrowing costs.

And companies carrying enormous financial obligations were particularly vulnerable. That’s what worried me in August.

Look, CoreWeave has real customers and an enormous backlog of contracted business. Some investors see a tremendous opportunity after this decline.

Fine.

But there’s a difference between having billions in business lined up and having the financial strength to deliver it profitably. And when you borrow heavily to fund growth, you don’t have much room for things to go wrong.

Here’s another thing I told viewers on Thursday. I wouldn’t make a new bearish trade on CoreWeave at $61.

The stock has already been punished. Could it go lower? Absolutely. But a good warning in August doesn’t automatically make it a good bearish trade in October.

Being right about the problem doesn’t automatically make every price a good place to bet against it. The trade has to make sense too.

That’s why I always want to know my risk before entering a trade.

What the Big Money Is Telling Us

Think back to that natural gas leak in California.

I didn’t predict the disaster. I figured out which publicly traded company was exposed and found unusual trading activity that suggested an opportunity.

With CoreWeave and Oracle, the setup was different. I was looking at financial risks building underneath two popular AI stocks.

But the principle is the same: Don’t just watch the headlines. Follow the money.

That’s the approach behind my premium trading service. We watch for unusual trading activity – large trades that stand out from the normal buying and selling.

Not every big trade means something, and not every trade works out. But when somebody puts serious money behind an unusual position, I want to know about it.

Then we look for an opportunity where we can define our risk before putting money on the line.

That’s the approach I share in my free $10K to $100K Challenge presentation, which went up just a couple of days ago.

In it, we go over how I look for unusual trading activity, evaluate opportunities, and manage risk as we pursue the possibility of turning $10,000 into $100,000 in 12 months.

It’s an ambitious goal, and I won’t pretend otherwise. But you can learn the process.

But you can learn the process. And you can learn to look beyond the stock price for signs of what might happen next.

Go here to learn more about my strategy.

Jonathan Rose

Founder, Masters in Trading

The post The AI Warning That Could Lead to Your Next Trading Opportunity appeared first on InvestorPlace.

Here’s why I’m handing today’s issue to Jonathan Rose: he called it. Back in August – with CoreWeave trading near $106 – Jonathan went on his live show and named it and Oracle as the two AI stocks most exposed if the market turned. He even titled the episode “AI House of Cards.” And he wasn’t guessing.

After years trading on the Chicago exchange floors, Jonathan watches signals most stock investors never check – like what it costs a company to borrow money. Those signals were flashing in August. The stock market caught up this week. Below, he tells the story of how he spotted it and how you can learn to see the same warnings before the crowd does.

One more thing: Jonathan just released his free $10K to $100K Challenge presentation, where he lays out the full strategy – how he finds unusual trading activity, evaluates the opportunity, and defines his maximum risk before entering any trade. Watch it after you read this; it’ll make even more sense then.

Now, here’s Jonathan.

In October 2015, a natural gas well near Los Angeles started leaking methane.

And I don’t mean a little leak. This thing was a catastrophe.

The leak came from an underground storage facility tucked into the mountains just above LA’s sprawling San Fernando Valley. Soon, a rotten-egg stench was drifting through nearby neighborhoods. 

Residents reported headaches, nausea, and nosebleeds. Thousands of families fled to hotels and temporary housing, with no idea when they could return. Two local schools had to be relocated.

The leak wouldn’t be stopped for 111 days.

But something about the coverage bothered me. Every article talked about Southern California Gas Co.

OK. But I had an additional question: Who owned SoCalGas?

The Important Company Wasn’t the One in the Headlines 

Turns out the parent company was Sempra (SRE), a publicly traded utility.

I pulled up Sempra on my screener and found something that stopped me cold. Somebody had made an unusually large bearish trade against the company.

I had two pieces of information: a major environmental disaster involving a Sempra subsidiary… and a big bearish trade in the parent company’s stock.

I didn’t know who placed that trade or what they knew. But I’d spent years trading on the floors of the Chicago exchanges, where I learned to pay attention when large trades show up in unusual places.

Somebody was putting real money behind a bet that Sempra was going lower.

So I shared a bearish trade of my own with my followers. With it, we risked $200 for the opportunity to make $4,800.

A few days later, California declared a state of emergency, and Sempra’s stock plunged. One of my followers later told me he’d made $9,600 after risking $400.

Here’s another part I love.

I found a reporter covering the leak who hadn’t mentioned Sempra, so I reached out and pointed out that SoCalGas had a publicly traded parent company. She wrote back that she was working on a follow-up.

That’s what I mean when I talk about following the money.

While everybody was watching the gas leak, I was watching the company behind it – and what traders were doing with its stock.

This August, I spotted something similar in a very different business: artificial intelligence.

Why CoreWeave and Oracle Looked Vulnerable Before the AI Selloff

On August 17, I was hosting my daily Masters in Trading LIVE show. We were talking about retail earnings and consumer health.

Then I changed the subject to two AI companies that had me worried: CoreWeave Inc. (CRWV) and Oracle Corp. (ORCL).

Now, I’m still very bullish on AI. I love what Nvidia Corp. (NVDA) is doing. I think artificial intelligence will create enormous opportunities for years to come.

But that doesn’t make every AI company a good investment.

CoreWeave and Oracle were borrowing enormous amounts of money to build AI infrastructure.

CoreWeave rents computing power to AI companies. That means buying expensive chips, building data centers, and spending a fortune before all that equipment generates revenue.

Oracle is making its own enormous investments in AI data centers, with a substantial portion of its future business tied to OpenAI.

Then there’s what’s called “circular financing.”

Nvidia sells chips to CoreWeave. Nvidia also owns a stake in CoreWeave. AI companies sign massive agreements to rent computing capacity. The companies providing that capacity borrow money to buy more equipment.

Big AI Contracts Don’t Eliminate Financing Risk

Everybody announces another billion-dollar deal, and investors get excited.

But I have a question: Where is all this money actually coming from?

When companies borrow billions and funnel money among the same group of businesses, those impressive deals can conceal a great deal of financial risk.

That’s why I called my August 17 show the AI House of Cards.

I told viewers that if the market turned, CoreWeave and Oracle would be among the first companies to get hit. I didn’t want to be long either stock. In fact, I suggested CoreWeave shareholders consider taking their profits.

CoreWeave was trading around $106 when I issued my warning.

CoreWeave’s Bond Market Flashed the Warning First

Now, I need you guys to stay awake for a minute. I’m going to talk about bonds.

I know, I know. Everybody’s favorite subject.

But this is important.

Most investors watching CoreWeave were looking at the stock price, Nvidia, and all those enormous AI deals. I was looking at what it cost CoreWeave to borrow money.

CoreWeave had issued bonds paying 9.6% interest, but those bonds were now trading at prices that pushed the yield to around 15%. That’s a massive jump.

That means investors were demanding much more compensation to take on CoreWeave’s risk. Somebody was getting nervous. And the warning appeared in the debt market before it became obvious in the stock price.

Oracle was showing warning signs, too. The cost of insuring its debt against default had risen sharply.

When you’re borrowing billions to build data centers, the cost of money matters. And when lenders get nervous, stockholders had better pay attention.

Then the AI Selloff Hit the Most Leveraged Name

On October 15, I revisited CoreWeave and Oracle during Masters in Trading LIVE.

CoreWeave had fallen from approximately $106 on August 17 to around $61. That’s a decline of roughly 42% in less than two months.

Oracle had taken a beating, too. Other AI infrastructure names were under pressure.

The immediate trigger wasn’t necessarily a new discovery about AI. Hotter-than-expected inflation raised concerns about interest rates and borrowing costs.

And companies carrying enormous financial obligations were particularly vulnerable. That’s what worried me in August.

Look, CoreWeave has real customers and an enormous backlog of contracted business. Some investors see a tremendous opportunity after this decline.

Fine.

But there’s a difference between having billions in business lined up and having the financial strength to deliver it profitably. And when you borrow heavily to fund growth, you don’t have much room for things to go wrong.

Here’s another thing I told viewers on Thursday. I wouldn’t make a new bearish trade on CoreWeave at $61.

The stock has already been punished. Could it go lower? Absolutely. But a good warning in August doesn’t automatically make it a good bearish trade in October.

Being right about the problem doesn’t automatically make every price a good place to bet against it. The trade has to make sense too.

That’s why I always want to know my risk before entering a trade.

What AI Stock Investors Can Learn From the Credit Market

Think back to that natural gas leak in California.

I didn’t predict the disaster. I figured out which publicly traded company was exposed and found unusual trading activity that suggested an opportunity.

With CoreWeave and Oracle, the setup was different. I was looking at financial risks building underneath two popular AI stocks.

But the principle is the same: Don’t just watch the headlines. Follow the money.

That’s the approach behind my premium trading service. We watch for unusual trading activity – large trades that stand out from the normal buying and selling.

Not every big trade means something, and not every trade works out. But when somebody puts serious money behind an unusual position, I want to know about it.

Then we look for an opportunity where we can define our risk before putting money on the line.

That’s the approach I share in my free $10K to $100K Challenge presentation, which went up just a couple of days ago.

In it, we go over how I look for unusual trading activity, evaluate opportunities, and manage risk as we pursue the possibility of turning $10,000 into $100,000 in 12 months.

It’s an ambitious goal, and I won’t pretend otherwise. But you can learn the process.

But you can learn the process. And you can learn to look beyond the stock price for signs of what might happen next.

Go here to learn more about my strategy.

The post How a 15% Bond Yield Warned of CoreWeave’s 42% Slide appeared first on InvestorPlace.

Veteran trader Jonathan Rose, editor of Advanced Notice, would probably tell you to resist that temptation – at least until you’ve done a little more homework.

In today’s Friday Digest takeover, Jonathan uses a remarkable recent biotech rally to illustrate one of the most important distinctions in trading: A company can have terrific news, a promising future, and plenty of institutional buying interest… yet still be a lousy trade at the current price.

That’s especially relevant in biotech, where clinical trial results and FDA decisions can send stocks soaring – or plunging – almost overnight.

So, today, Jonathan explains how he uses the FDA’s calendar, unusual options activity, and a handful of trading rules to separate opportunities worth pursuing from stocks he’d rather leave alone. Along the way, he highlights three biotech companies he’s watching closely and explains why he’s passing on another highflyer.

It’s the same disciplined approach Jonathan detailed this past Wednesday night in his free $10K to $100K Challenge event, where he walked through the signals, tools, and risk-management principles behind his trading strategy. You can watch the replay right here.

Bottom line: finding the right stock is only half the battle. Knowing when – and whether – to trade it can be just as important.

I’ll let Jonathan take it from here.

Have a good evening,

Jeff Remsburg

You’re running late to a movie you’ve been waiting months to watch. But when you go from a bright lobby and into the theatre, you can’t see a thing.

You squint when you enter, and walk slowly up the stairs as you look for an empty seat. When you finally spot one, you find yourself apologizing as you step on the feet of the other movie-goers who came on time.

By the time you sit down, your shoes are sticky because you couldn’t see the pool of soda on the floor that hadn’t been cleaned up after the previous showing.

When we step out of a bright place and into a dark room, it takes 15 minutes for our eyes to adjust to the dark.

That same period of adjustment from light to dark is how long it took the options market to catch up to what FDA trial data already showed.

On September 28, Kodiak Sciences Inc. (KOD) put out positive Phase 3 data on its DAYBREAK trial. The trial was designed to address a condition known as wet age-related macular degeneration — an eye condition that causes blurred vision or reduced central vision.

KOD’s two experimental eye drugs — Zenkuda and tarabirafusp-ted — proved capable against the current standard of care, aflibercept, at just one year. Even better, 54% of patients actually hit durability at just six months. That’s the number that actually tells you whether a drug holds up once the trial ends.

The stock didn’t just drift higher on the news. It exploded. Shares of Kodiak gapped up as much as 177.96% that day on 38.46 million shares traded — more than 54 times its roughly 701,000-share average volume.

That’s not a retail headline-chase. That’s the kind of volume that only shows up when institutional money decides it needs to own a name right now, all at once.

Zoom out and the full move is even bigger. KOD has run from around $22 back in February to over $98 today against a $5.94 billion market cap — a gain of more than 300% in under a year.

But here’s the part most traders miss: A gap that big doesn’t automatically mean the trade is still good. Proof is not the same thing as entry.

The science behind KOD’s durability data can be exactly right while the stock, sitting 178% above where it opened that morning, is temporarily the wrong price to pay.

What I want to see now isn’t another headline — it’s fresh demand showing up after the stock consolidates, not late money chasing premium into spreads that have already blown out.

And I believe KOD — along with a whole basket of AI-driven biotech names I’ve been tracking — could gain even more momentum from here, based on one of biotech’s best gauges of all: the PDUFA calendar.

Today, I’ll explain what the PDUFA calendar is, the catalysts my system is flagging that could boost three biotech stocks higher, and the popular biotech name I’m avoiding right now.

I’ll also explain how this ties into my $10K to $100K Challenge event, which aired earlier this week. You can watch the replay here.

Investors Watch These FDA Dates Like Hawks

PDUFA stands for Prescription Drug User Fee Act. Basically, it tracks when the FDA makes decisions on new drugs.

Think of it like earnings season but for biotech. Every time a PDUFA date hits, a biotech stock either soars or tanks based on whether the FDA approves their drug.

Here’s the best part: You know these dates months in advance.

Advisory committees meet. They evaluate the drug. They vote. And the FDA almost always follows their recommendation.

It’s not a surprise. It’s scheduled and predictable.

And over the next few months, we’ve got a wave of PDUFA dates coming — everything from skin cancer treatments to digestive disease medications. And many of these companies are already pulling in massive government funding as AI makes their research faster and cheaper.

That’s exactly why I’ve been watching biotech all through 2026. These names don’t move in lockstep with the Nasdaq Composite, the AI trade, or the hyperscalers.

But they share something even more valuable to a trader like me: smaller market caps, and a lot of volatility.

The clinical and regulatory milestones we see on the calendar create catalysts the options market can price faster than the broader stock market. So whenever a PDUFA date hits, it can cause a stock to reprice in a single session. The signal isn’t just price. It’s participation.

And when price, volume, and liquidity arrive together, that hands us the sort of volatility that makes the smaller names in this space move.

That’s the exact dynamic I’m highlighting today in three stocks I’m watching — plus the one I’m passing on that could still be a great trade after another catalyst hits.

Stock No. 1: BioMarin Pharmaceutical Inc. (BMRN)

BioMarin pairs a real AI catalyst with a business that’s already proven itself. The company has built a system to screen AI-generated enzyme candidates for its rare-disease pipeline — treatments for conditions with no cure today, from rare skeletal disorders to Duchenne Muscular Dystrophy.

The pipeline is promising. The stock, lately, hasn’t been.

I actually flagged BMRN on my daily show, Masters in Trading LIVE, a few weeks ago during its most recent pullback. At the time, it was trading around $57.40, with an expected move near $57.79 — that’s the range options traders are pricing in for the stock, based on how the options themselves are priced.

Here’s why that number matters: over the last three years, BMRN has stayed inside that expected range about 80% of the time.

Over the last two years, it’s been even tighter — 87.5%. That tells me the options market has done a solid job pricing this stock’s moves. Right now, without a fresh data point to push it, BMRN is sitting toward the bottom of that range.

But don’t mistake “quiet” for “ignored.” Institutional money is still positioning here as BMRN heads toward new trial results and a PDUFA date in January 2027.

If we start seeing a clear imbalance in trading activity ahead of that date, that’s worth watching closely.

Stock No. 2: Precigen (PGEN)

Precigen just landed an FDA platform-technology designation for its AdenoVerse platform — the same technology behind its already-approved product, PAPZIMEOS.

Translate that into plain English: the FDA is letting Precigen reuse what it already proved works — its manufacturing know-how, its preclinical data — instead of rebuilding that case from scratch every time. One validated platform, multiple shots on goal.

That’s exactly what’s playing out with PRGN-2012, Precigen’s treatment for adults with recurrent respiratory papillomatosis (RRP) — a rare disease that causes benign tumors to grow in the respiratory tract.

Since clearing its PDUFA date late last year, PGEN has ripped higher — up 104.31% year-to-date.

There’s no confirmed PDUFA date left on the calendar for 2026, but don’t read that as a quiet stretch. I expect this early win to open the door to more drug applications working their way through the pipeline.

Momentum here is real. Entry discipline still matters.

Stock No. 3: Absci Corp. (ABSI)

If you want to see AI actually designing a drug — not just assisting with one — this is the name.

Absci’s ABS-201 was built by generative AI from the ground up. It’s an antibody treatment targeting endometriosis, and the company’s planning a global Phase 2 study of roughly 150 patients across 10-plus countries, with the trial set to kick off around mid-2027, pending regulatory sign-off.

No PDUFA date on the board for the rest of this year — that comes later. But 2027 is shaping up to be a busy one.

In the meantime, ABSI is already up 217.19% year-to-date, on a $1.84 billion market cap. That’s small enough to move fast on a headline, and big enough that institutions are already paying attention.

Stock to Avoid: Moderna Inc. (MRNA)

Here’s where discipline actually matters.

Moderna shares are up 566.94% over the past year — a number that would make almost any trader want in. But MRNA’s market cap sits at $75.86 billion, well outside our under-$50 billion screen.

A great story that breaks the rules is still a pass — and that discipline is exactly what keeps a 300% gap-up day like KOD’s from turning into an account-blowing mistake.

What to Look for in Unusual Options Activity

When it comes to AI biotech stocks, here’s what I’m always screening for:

• Premium meaningfully above a name’s normal trading activity
• Trading volume that exceeds open interest, with spot confirming the direction
• Expirations that line up with a known catalyst — not just zero-day noise

Unusual trading activity is only one piece of the puzzle. You still need to understand the company, the catalyst, the stock’s price action, the options’ liquidity, and the amount you’re willing to risk before any of this means anything.

We have AI rapidly overhauling the process of making life-saving drugs. And with this many potential approvals lined up on the calendar, we’ve got a series of catalysts that could send any of these names surging higher from here.

During my recent $10K to $100K Challenge event, I show you how to set up in the next wave of AI names and the system I use to find those names in the first place. I also reveal a simple strategy that could help you turn every $10,000 into $100,000.

As you’ll come to understand when watching the $10K to $100K Challenge, I’m not one to make lofty or false promises. Instead, my success — and the success of my readers — is anchored by a simple strategy I perfected while working as a market maker on the floor of the Chicago Mercantile Exchange. This strategy works in bull markets and bear markets…

And it doesn’t matter what’s happening with AI, interest rates, midterm elections, you name it. The same process underpins every trade I make.

Click here to check out my $10K to $100K Challenge. 

Remember, the creative trader wins.

Jonathan Rose

Founder, Masters in Trading

The post The FDA Calendar Smart Money Never Ignores appeared first on InvestorPlace.

My friend and colleague Jonathan Rose has been tracking that shift across the biotech sector all year. And today, I’ve invited him to show you how a trader reads that shift once a stock has already made its move, why a 178% gap-up isn’t automatically a buy and why the FDA’s own calendar can tell you more than the headlines ever will.

That’s also why I encourage you to watch Jonathan’s $10K to $100K Challenge. For those of you who joined him, you learned how a specific type of trade can magnify a stock’s move in either direction, why he pays attention to the expiration dates on unusual trades and how his screening tools help him narrow a flood of market data into opportunities worth investigating.

Missed the presentation? You can still join Jonathan’s challenge. You don’t need $10,000 to get started, either. He explains how to begin with smaller trades, including setups where you can keep the amount at risk below $500.

Click here to watch the presentation and learn how to take part.

But first, read on for the three AI biotech stocks Jonathan is tracking right now…

***********************

You’re running late to a movie you’ve been waiting months to watch. But when you go from a bright lobby and into the theatre, you can’t see a thing.

You squint when you enter, and walk slowly up the stairs as you look for an empty seat. When you finally spot one, you find yourself apologizing as you step on the feet of the other movie-goers who came on time.

By the time you sit down, your shoes are sticky because you couldn’t see the pool of soda on the floor that hadn’t been cleaned up after the previous showing.

When we step out of a bright place and into a dark room, it takes 15 minutes for our eyes to adjust to the dark.

That same period of adjustment from light to dark is how long it took the options market to catch up to what FDA trial data already showed.

On September 28, Kodiak Sciences Inc. (KOD) put out positive Phase 3 data on its DAYBREAK trial. The trial was designed to address a condition known as wet age-related macular degeneration. It’s an eye condition that causes blurred vision or reduced central vision.

KOD’s two experimental eye drugs, Zenkuda and tarabirafusp-ted, proved capable against the current standard of care, aflibercept, at just one year. Even better, 54% of patients actually hit durability at just six months. That’s the number that actually tells you whether a drug holds up once the trial ends.

The stock didn’t just drift higher on the news. It exploded. Shares of Kodiak gapped up as much as 177.96% that day on 38.46 million shares traded. That’s more than 54 times its roughly 701,000-share average volume.

That’s not a retail headline-chase. That’s the kind of volume that only shows up when institutional money decides it needs to own a name right now, all at once.

Zoom out and the full move is even bigger. KOD has run from around $22 back in February to over $98 today against a $5.94 billion market cap. We’re talking a gain of more than 300% in under a year.

But here’s the part most traders miss: A gap that big doesn’t automatically mean the trade is still good. Proof is not the same thing as entry.

The science behind KOD’s durability data can be exactly right while the stock, sitting 178% above where it opened that morning, is temporarily the wrong price to pay.

What I want to see now isn’t another headline. I want to see fresh demand showing up after the stock consolidates, not late money chasing premium into spreads that have already blown out.

And I believe KOD, along with a whole basket of AI-driven biotech names I’ve been tracking, could gain even more momentum from here, based on one of biotech’s best gauges of all: the PDUFA calendar.

Today, I’ll explain what the PDUFA calendar is, the catalysts my system is flagging that could boost three biotech stocks higher, and the popular biotech name I’m avoiding right now.

I’ll also connect those ideas to the approach I shared in Wednesday’s $10K to $100K Challenge event.

There’s still time to join my challenge. Click here to watch the presentation and get the details.

Investors Watch These FDA Dates Like Hawks

PDUFA stands for Prescription Drug User Fee Act. Basically, it tracks when the FDA makes decisions on new drugs.

Think of it like earnings season but for biotech. Every time a PDUFA date hits, a biotech stock either soars or tanks based on whether the FDA approves their drug.

Here’s the best part: You know these dates months in advance.

Advisory committees meet. They evaluate the drug. They vote. And the FDA almost always follows their recommendation.

It’s not a surprise. It’s scheduled and predictable.

And over the next few months, we’ve got a wave of PDUFA dates coming. Everything from skin cancer treatments to digestive disease medications. And many of these companies are already pulling in massive government funding as AI makes their research faster and cheaper.

That’s exactly why I’ve been watching biotech all through 2026. These names don’t move in lockstep with the Nasdaq Composite, the AI trade, or the hyperscalers.

But they share something even more valuable to a trader like me: smaller market caps, and a lot of volatility.

The clinical and regulatory milestones we see on the calendar create catalysts the options market can price faster than the broader stock market. So whenever a PDUFA date hits, it can cause a stock to reprice in a single session. The signal isn’t just price. It’s participation.

And when price, volume, and liquidity arrive together, that hands us the sort of volatility that makes the smaller names in this space move.

That’s the exact dynamic I’m highlighting today in three stocks I’m watching, plus the one I’m passing on that could still be a great trade after another catalyst hits.

Stock No. 1: BioMarin Pharmaceutical Inc. (BMRN)

BioMarin pairs a real AI catalyst with a business that’s already proven itself. The company has built a system to screen AI-generated enzyme candidates for its rare-disease pipeline. These are treatments for conditions with no cure today, from rare skeletal disorders to Duchenne Muscular Dystrophy.

The pipeline is promising. The stock, lately, hasn’t been.

I actually flagged BMRN on my daily show, Masters in Trading LIVE, a few weeks ago during its most recent pullback. At the time, it was trading around $57.40, with an expected move near $57.79. That’s the range options traders are pricing in for the stock, based on how the options themselves are priced.

Here’s why that number matters: over the last three years, BMRN has stayed inside that expected range about 80% of the time.

Over the last two years, it’s been even tighter at 87.5%. That tells me the options market has done a solid job pricing this stock’s moves. Right now, without a fresh data point to push it, BMRN is sitting toward the bottom of that range.

But don’t mistake “quiet” for “ignored.” Institutional money is still positioning here as BMRN heads toward new trial results and a PDUFA date in January 2027.

If we start seeing a clear imbalance in trading activity ahead of that date, that’s worth watching closely.

Stock No. 2: Precigen (PGEN)

Precigen just landed an FDA platform-technology designation for its AdenoVerse platform, the same technology behind its already-approved product, PAPZIMEOS.

Translate that into plain English: the FDA is letting Precigen reuse what it already proved works – its manufacturing know-how, its preclinical data – instead of rebuilding that case from scratch every time. One validated platform, multiple shots on goal.

That’s exactly what’s playing out with PRGN-2012, Precigen’s treatment for adults with recurrent respiratory papillomatosis (RRP) – a rare disease that causes benign tumors to grow in the respiratory tract.

Since clearing its PDUFA date late last year, PGEN has ripped higher – up 104.31% year-to-date.

There’s no confirmed PDUFA date left on the calendar for 2026, but don’t read that as a quiet stretch. I expect this early win to open the door to more drug applications working their way through the pipeline.

Momentum here is real. Entry discipline still matters.

Stock No. 3: Absci Corp. (ABSI)

If you want to see AI actually designing a drug – not just assisting with one – this is the name.

Absci’s ABS-201 was built by generative AI from the ground up. It’s an antibody treatment targeting endometriosis, and the company’s planning a global Phase 2 study of roughly 150 patients across 10-plus countries, with the trial set to kick off around mid-2027, pending regulatory sign-off.

No PDUFA date on the board for the rest of this year – that comes later. But 2027 is shaping up to be a busy one.

In the meantime, ABSI is already up 217.19% year-to-date, on a $1.84 billion market cap. That’s small enough to move fast on a headline, and big enough that institutions are already paying attention.

Stock to Avoid: Moderna Inc. (MRNA)

Here’s where discipline actually matters.

Moderna shares are up 566.94% over the past year – a number that would make almost any trader want in. But MRNA’s market cap sits at $75.86 billion, well outside our under-$50 billion screen.

A great story that breaks the rules is still a pass – and that discipline is exactly what keeps a 300% gap-up day like KOD’s from turning into an account-blowing mistake.

What to Look for in Unusual Options Activity

When it comes to AI biotech stocks, here’s what I’m always screening for:

• Premium meaningfully above a name’s normal trading activity
• Trading volume that exceeds open interest, with spot confirming the direction
• Expirations that line up with a known catalyst – not just zero-day noise

Unusual trading activity is only one piece of the puzzle. You still need to understand the company, the catalyst, the stock’s price action, the options’ liquidity, and the amount you’re willing to risk before any of this means anything.

We have AI rapidly overhauling the process of making life-saving drugs. And with this many potential approvals lined up on the calendar, we’ve got a series of catalysts that could send any of these names surging higher from here.

That’s why I held my free $10K to $100K Challenge presentation on Wednesday.

I walked through the process I use to turn unusual trading activity into potential opportunities – and explained why you don’t need to start with $10,000 to learn it.

My goal is ambitious: to show you a strategy I believe could help you turn $10,000 into $100,000 or more over the next year. That’s a goal, not a guarantee. Every trade carries risk.

Even better, there’s still time to join my challenge.

You can watch the presentation now to see the approach I developed over decades on professional trading floors. I explain how I look for opportunities in both rising and falling markets, why I recommend starting small, and how I decide what I’m willing to risk.

Whether I’m looking at AI, biotech, interest rates, or another market story, the same process underpins every trade I make.

Click here to watch the $10K to $100K Challenge presentation and learn how to get started.

And remember, the creative trader wins

Jonathan Rose

Founder, Masters in Trading

The post The “Calendar Trick” for Huge Biotech Gains – And 3 Stocks I’m Watching appeared first on InvestorPlace.

On Monday, Sept. 28, SpaceX (SPCX) sent Starship into orbit for the first time.

Three days later, Google (GOOGL) confirmed that its first Project Suncatcher prototype was online and operating in space.

The Falcon 9 mission that carried Google’s prototype also hauled two more unusual payloads. One is designed to beam power from one satellite to another. The other will test whether solar energy collected in orbit can be sent back to Earth.

Then, that Friday, Amazon (AMZN) warned that more than 100 communities are considering moratoriums on new data centers.

That is a lot of movement in four days.

We have spent months writing about why orbital computing could eventually make sense. We have studied the cost curve, the engineering challenges, the SpaceX–Nvidia strategy, and the companies building around it.

The story is promptly picking up its pace.

Orbital Data Centers Are Moving From Theory to Hardware

When we first broke down Google’s Project Suncatcher roadmap, the whole thing was still on paper.

Google now has hardware in orbit.

The company says its prototype satellite, built with Planet Labs (PL), successfully established contact after launch and is operating as expected. Over the coming weeks, Google will test how its Tensor Processing Units (TPUs) handle the physical stress of spaceflight, radiation, and extreme thermal conditions.

This is still a small research mission.

One test satellite is a long way from an orbital data center. It will not train the next Gemini model or replace one of Google’s giant terrestrial computing campuses.

Its job is more basic.

Does the hardware survive launch? How does it perform under radiation? Can the system manage the enormous swings in temperature? Which parts fail first?

Those questions are difficult to answer inside a laboratory. Eventually, the equipment has to fly – and now it is.

This will give Google real operating data from real hardware in the environment where a future system would have to work.

The results will shape the next design. They will also begin revealing which components can move forward largely unchanged and which ones require a complete rethink.

That’s how a science project turns into a parts list. 

Orbital Data Centers Will Need Their Own Power Infrastructure

Getting a chip to orbit is one thing. Running it is another. 

A powerful AI satellite also needs electricity, and the amount required can change dramatically from one moment to the next.

Today, each spacecraft generally brings its own solar arrays and batteries. Engineers size that equipment around the satellite’s expected peak workload, which adds mass and limits what the machine can do.

A shared power network could change that equation.

Star Catcher Wants to Sell Power as a Service in Orbit 

Star Catcher’s new Protostar satellite is designed to harvest energy, locate another free-flying spacecraft, and transmit power to it. After commissioning, Protostar plans to deploy a CubeSat and beam energy into ordinary solar panels attached to that second spacecraft.

If the experiment works, Star Catcher says it would mark the first optical power transfer between two untethered spacecraft. 

In other words, one satellite would act like a power station for another.

That could eventually allow computing satellites to draw extra electricity during demanding workloads without carrying every panel and battery themselves. Power generation could sit in one part of a constellation while compute sits somewhere else.

And customers aren’t waiting for the demo.

Star Catcher has announced 10 power-purchase agreements with space companies, more than 40 letters of intent, and a $60 million strategic-funding award from the U.S. Space Force. Those agreements may not guarantee a profitable orbital grid; but they show that spacecraft operators are already thinking seriously about buying power as a service.

The Transporter-18 mission carried another energy experiment, too.

Reason-1, built by Cowboy Space, is designed to collect solar energy in orbit and test sending it toward Earth. Founder Baiju Bhatt has described the long-term idea as something like Starlink for power: an orbital network that could deliver electricity to areas without a dependable terrestrial grid.

Both concepts are still highly experimental.

Power can be lost during transmission. Hardware has to be extremely precise. Regulators will surely have plenty to say about beams traveling between spacecraft or toward Earth. And the economics are nowhere near proven.

But those questions are now being answered in orbit instead of argued in conference rooms.

Starship Just Took a Big Step Toward Orbital Freight

None of this matters if you can’t get the stuff up there – and “the stuff” is heavy. An orbital AI system isn’t just chips. It’s radiators the size of billboards, batteries, shielding, solar arrays, laser links – tons of hardware that has to survive launch and arrive in exactly the right orbit, again and again.

Which is why the quietest big deal happened on Sept. 28.

That’s when SpaceX’s 14th Starship test became the vehicle’s first true orbital mission. It also deployed 26 next-generation Starlink V3 satellites, giving the rocket its first meaningful orbital payload.

Reaching Orbit Is Only the First Test

That doesn’t mean the mission was perfect, though. One booster engine shut down during ascent. After additional engine trouble, SpaceX shortened the planned flight from about 10 hours to roughly three. The upper stage ended its mission with a fiery Pacific splashdown.

Rapid reusability is questionable. So is the long-term launch cost.

But Starship completed two jobs orbital infrastructure desperately needs:

It reached orbit, and it released a large payload.

Previous flights proved that the vehicle could survive parts of the journey. Flight 14 showed it has the potential to become a freight system.

Musk is now targeting a Starship cadence of one or two launches per week next year. He also says SpaceX and Tesla are aiming for 200 gigawatts of annual solar-production capacity, partly because solar panels can generate much more consistently in space than they can on Earth.

Starship still has to demonstrate reflight, orbital refueling, safe recovery, and dependable operations before a weekly cadence becomes realistic.

Take the targets with a grain of salt. Musk’s timelines always need some. But even discounted, they sketch the size of the machine he’s assembling: industrial-scale solar production and enormous amounts of computing hardware operating beyond Earth. 

Earth Is Adding Urgency

The case for orbital AI does not depend on terrestrial data centers disappearing. They will remain the center of the computing world for years.

But adding new capacity on Earth is becoming more expensive, political, and time-consuming.

Amazon just committed more than $1 billion over five years to communities that host its data centers. The company says the money will support education, workforce training, energy affordability, and water and energy conservation. It also pledged to stop using nondisclosure agreements with government agencies around new projects. 

This comes as communities are raising concerns over electricity prices, water consumption, construction, noise, local benefits, and the lack of transparency around some projects. AWS chief Matt Garman says more than 100 data-center moratoriums are now being considered across the United States. 

Amazon is spending money to keep the terrestrial buildout moving.

Google is now collecting data from the first hardware designed to explore an alternative.

Orbit doesn’t get cheaper just because a town says no to another server farm. But every “no” makes an alternative worth a little more. 

A computing platform that can add capacity without competing for a local grid connection, a water permit, or a zoning approval could eventually solve a very expensive problem.

That future is still years away. But the pressure creating it is already here.

The Bottom Line: Orbital Data Centers Have Entered the Prototype Phase

A few months ago, orbital computing was mostly an argument about future economics.

Then SpaceX chose Nvidia hardware for Starmind. Google put Project Suncatcher on a launch schedule. Startups began raising money around orbital power.

Now Starship has reached orbit with a meaningful payload.

Google’s first prototype is alive in space.

And two power experiments are beginning the work required to test an orbital energy network.

The economics remain unresolved, the engineering difficult.

Many of these experiments will probably disappoint. Some may fail completely.

But a concept becomes a prototype. A prototype creates supplier requirements. Successful tests turn into larger programs, manufacturing schedules, and orders.

And when those orders start flowing, I want us positioned before them – which is the whole point of what I call XPANSE.

It’s my name for Elon Musk’s next great project – one Silicon Valley insiders peg at $126 trillion in potential impact, and one a Berkeley- and Harvard-trained physicist calls “the greatest transition in history.” 

Those are grand claims. But you just read the receipts: chips alive in orbit, power beaming between satellites, Starship hauling freight. The transition is leaving the whiteboard.

My free XPANSE briefing breaks down the full picture – including the three moves I’d make right now and one $15 stock I believe sits at the center of it all. You’ll get its name and ticker just for watching.

Get positioned while this is still called an experiment.

Check out the bull thesis behind XPANSE.

The post Google Is Testing AI In Orbit as 100 Communities Rethink Data Centers appeared first on InvestorPlace.

Last night, my colleague Jonathan Rose held his free $10K to $100K Challenge event. The early feedback has been overwhelmingly positive, with viewers praising both Jonathan’s approach to trading and his gift for explaining it clearly.

So, today, I want to let you see for yourself what all the buzz is about. And as you’ll see below, Jonathan’s approach just delivered for his subscribers again this morning.

Last week, I sat down with Jonathan for an in-depth interview for Investing Insider, the other InvestorPlace newsletter I helm. I came away from that conversation with a notepad full of ideas – and a few things that changed how I’m looking at today’s market, both its risks and its opportunities.

In the wake of last night’s event, I decided Digest readers should see that interview, too. And the timing here is important…

The 10-year Treasury yield recently hit its highest level since 2002 – right on the heels of stocks hitting new all-time highs. Jonathan called that kind of disconnect something that “can’t last.” And right on cue, the market has faced heavy selling pressure over the last few days after our interview.

So, what happens from here? And how should you be positioned for it?

That’s where our conversation started. But here are some of the additional topics we covered:

• The bond market warning that’s “scaring” Jonathan right now – and why most investors staring at record stock prices aren’t paying attention to it
• Exactly what he will do if the Nasdaq drops 5% (hint: he’s not running for the exits)
• Why he expects more Fed rate hikes – and why that’s not a guess, but a read of what big money is already betting on
• The one corner of the market he’s avoiding until rates come down – it may be sitting in your portfolio right now
• His three favorite sectors heading into year-end – with specific stock names in each
• How he uses options to cap his maximum loss before he ever enters a trade – the part of options trading most people get backward

There’s plenty more in this candid, fast-moving conversation, and you’ll walk away with specific ideas you can use right away.

After the interview, go deeper with last night’s free replay

There’s only so much ground Jonathan and I could cover in our conversation. Last night, Jonathan had the whole evening – and he used it.

In his $10K to $100K Challenge, he walked through the full strategy behind his approach:

• How he spots unusual trading activity – and separates the meaningful signals from the noise
• How he combines that activity with Marc Chaikin’s Money Flow data before making a recommendation
• How he plans each trade, including what he’s willing to risk, before he enters it
• Why his approach can work with recommended trades costing less than $500 to enter

And yes, he explains the thinking behind the challenge’s name: his goal to show everyday investors how they could potentially turn $10,000 into $100,000 using his approach.

A Triple-Digit Example From This Morning

Speaking of how Jonathan thinks through a trade – he just gave us a perfect example.

Ahead of FMC Corp.’s (FMC) earnings, Jonathan recommended his subscribers buy both calls and puts on the stock. That’s a way to position for a big move without having to guess which direction it will go. As Jonathan put it:

We don’t have to predict which direction the stock will go to benefit from a significant move.

This morning, the move came. FMC dramatically lowered its third-quarter outlook – it now expects revenue of just $65 million to $125 million, down from a previous forecast of $840 million to $900 million. Shares plunged more than 36%.

So, Jonathan told his subscribers to take profits on the puts. Here’s how he described the result:

Our [put options have] given us more than 200% on our total position from this sharp decline, and I don’t want to get greedy after a move of this magnitude.

His members were quick to share their results…

(If you can’t see the screenshot below, subscribers are reporting gains of between 280% to 752%.)

That’s the kind of strategy Jonathan walked through in last night’s event.

Bottom line: If you’ve ever wanted to see how a former market maker and trading pro thinks through a trade from start to finish, this is it.

If you missed it last night, you haven’t missed out. The free replay is up and available to watch right here.

So, enough introduction. Click here to watch our interview or click the thumbnail below.

Then, watch the free replay of Jonathan’s $10K to $100K Challenge right here.

We’ll be back with our usual Digest tomorrow.

Have a good evening,

Jeff Remsburg

The post “This Darn Bond Market Is Scaring Me” appeared first on InvestorPlace.

Those who tuned in learned…

• How Jonathan uses unusual trading activity to follow big investors’ moves.
• Why Volatility like we’ve seen lately can create big trading opportunities, if you know where to look.
• How Jonathan structures trades with a defined maximum risk. And much more…

Missed it? Don’t worry. There’s still time to join Jonathan’s challenge. Watch the presentation here to see his strategy and get the details.

Jonathan has spent 28 years in professional trading, and I appreciate how he makes that experience useful and understandable to everyday investors.

Below, he looks beyond Elon Musk’s Neuralink to two public companies on his watchlist. And he explains what interests him and where the connections and risks differ.

Take it away, Jonathan…

*********************************

In 2024, a man was diagnosed with amyotrophic lateral sclerosis. The ALS – often called Lou Gehrig’s disease – took away his ability to speak.

The subject, Terry, was desperate to find an answer that would allow him to regain his speech.

Then he joined a clinical trial at Neuralink, Elon Musk’s company developing devices that let the brain communicate directly with a computer.

These devices are called brain-computer interfaces, or BCIs. In Terry’s case, the goal was to turn the brain signals involved in speaking into words a computer could say aloud.

And it worked. Using the implant and a computer-generated voice, Terry was able to tell his wife, “I love you.” ALS hadn’t restored his ability to speak naturally; the technology was speaking for him. But he could communicate those words again. Think about what that means for someone who has lost his voice.

If you’d like to invest in this medical innovation, though, you run into a problem: You can’t buy Neuralink on the stock market. It’s still private.

So where else can we look?

That’s the question I’ve been working through on my free show, Masters in Trading LIVE. Back in April, I shared a basket of 14 public companies to research around this developing field. Some make medical equipment. Others provide tools scientists use in their research. Their connections to brain-computer interfaces vary, and that matters when you’re deciding what to buy.

And there’s real money going into the field. OpenAI is backing Merge Labs, another company developing brain-computer interfaces. Synchron raised $200 million to advance its technology toward commercial use. Neuralink is getting plenty of attention, but other businesses are working on different ways to connect the brain to a machine.

Today, I’ll show you two public companies on my watchlist: one with a direct connection to a brain-interface developer, and another that makes research tools I’m following as a more speculative idea. I’ll explain why each interests me, what could drive the stock’s price, and the risks you need to understand.

You don’t have to wait for a Neuralink IPO to start researching opportunities around this field. But you do need to know what you own and why you own it.

A Small Research Company With a Big Launch Ahead

The first company I have my eye on is a small, highly volatile name that has already experienced some serious moves over the last year.

When I discussed it on my recent livestream, the stock had climbed from $0.72 to $1.20 in roughly two weeks. That’s about 67%. These small companies can move really quickly.

But a stock moving higher is only the start of the research. What does the company do? What’s changing? What could give it another reason to move?

Quantum-Si Inc. (QSI) makes equipment that helps scientists identify proteins by reading their building blocks. Proteins do much of the work inside our cells, and studying them helps researchers understand disease and develop treatments.

That puts QSI on the biological-research side of my watchlist. It’s a broader, more speculative idea than a company developing brain-interface hardware. I’m following its research tools and upcoming product launch. I’m not counting on a Neuralink contract or assuming that progress in brain interfaces will produce sales for QSI.

On the show, I also pointed out a jump in trading activity. About 20.5 million shares changed hands on September 29, compared with a daily average of about 2.85 million over the preceding 100 trading days. That’s more than seven times the usual activity.

That kind of change in volume is exactly the sort of thing I pay attention to.

When the volume changes, I want to know why. It doesn’t tell me that everyone buying is right, or that the stock will keep going up. But it does tell me there’s more activity to investigate.

And you need to understand how early this business still is. QSI reported just $344,000 in revenue last quarter. It had roughly $170 million in cash and investments at the end of June. And the launch of its next-generation protein-analysis equipment, called Proteus, has already slipped from late 2026 to the second quarter of 2027. It still has to deliver the equipment and build sales.

It’s an early, high-risk, high-reward bet. (Full disclosure: I hold a personal position in QSI.)

My approach with a company this small is to keep the position small enough that losing the entire investment wouldn’t hurt my financial plans. There’s room for significant growth if the business succeeds. There’s also a real chance it doesn’t.

The Chipmaker Helping Build Another Way Into the Brain

The second stock I want to show you has a direct connection to brain-computer interfaces – and has been one of my favorite small-cap healthcare names for a while now.

I’ve been walking through this one on Masters in Trading LIVE, because there’s more to the business than you might realize at first glance.

Here’s what makes Butterfly Network Inc. (BFLY) so interesting…

Butterfly puts ultrasound technology on a chip. That lets it make handheld scanners doctors can use to look inside the body, instead of relying on a large machine wheeled around a hospital.

But medical scans are only one use for that technology.

On September 1, Butterfly announced an agreement with Merge Labs. That’s the brain-interface company backed by OpenAI that I mentioned earlier. Merge will use Butterfly’s ultrasound chips to develop its own ways to communicate with the brain.

And it’s the connection I want you to understand. Butterfly has an actual agreement with a company developing brain interfaces. The deal includes payments for access to its technology, hardware purchases, and potential royalties if future products reach commercial sales. Butterfly can also license its technology to other companies in the field.

So we have a public company that could earn money helping other businesses build their devices. We can research it today, even while those developers remain private.

And Butterfly already has customers putting its chips to work beyond its handheld scanners.

Back in June, BFLY revealed that its chip is powering Midjourney’s new full-body imaging platform. That’s a scanner designed to use ultrasound to create images throughout the body.

Butterfly previously disclosed that the partnership could generate up to $74 million in payments over five years. That’s meaningful potential revenue from a single deal.

We’re also seeing progress in the numbers. Butterfly reported second-quarter revenue of $32.6 million, up 39% from a year earlier. Licensing its technology helped drive that growth. The company still reported a loss, so growing sales and becoming profitable are two separate things we need to watch.

That gives me something concrete to follow: Are its partners moving forward? Is Butterfly signing more agreements? And are those agreements turning into revenue?

And there’s another catalyst on the calendar: its next earnings report, expected on October 30. On my recent livestream, I showed viewers that traders were pricing in a substantial move around earnings.

But an expected move doesn’t tell you the direction. The stock can move sharply lower, too.

Stocks move when they have a reason to move. With Butterfly, we have business developments and an earnings report to investigate. Then we have to decide whether the opportunity is worth the risk and how much we’re comfortable putting into the trade.

Finding the Opportunity – and Planning the Trade

This is the work I do on Masters in Trading LIVE. We take an interesting story and start asking questions. What does the company actually sell? What could change its business? Why is trading activity picking up? And what are we risking if we’re wrong?

Finding a company worth watching is the beginning. Then we have to work through the trade.

That’s what I walked through yesterday, during my free presentation, the $10K to $100K Challenge. I explained the strategy behind some of my biggest trading opportunities. And, I showed how you can start putting that method to work.

Thanks to everyone who joined me! You saw how I follow unusual trading activity, look for opportunities in both rising and falling markets, and define my risk before entering a trade.

But if you missed it, no problem. There’s still time to join my challenge.

Click here to watch the $10K to $100K Challenge presentation and learn how to get started.

In the presentation, I also explain how you can participate without starting with $10,000, including trades you can enter for less than $500. You choose how much to put at risk, and you can lose the full amount you invest.

This is the strategy behind past recommended trades with gains like 779% on Occidental Petroleum Corp. (OXY) and 1,076% on Bristol-Myers Squibb Co. (BMY). Those are individual past results, but they show why I’m so excited to teach you the process.

I’ve spent 28 years in professional trading, starting at the Chicago Mercantile Exchange and later working as a market maker at the Chicago Board Options Exchange. What I want to do now is make those lessons useful to you.

For Terry, the promise of this technology is deeply personal: communicating again after ALS took away his ability to speak. His experience shows why researchers keep working on these devices and why investors are paying attention.

Our job as traders is to figure out which businesses can turn that progress into sales, and which trades make sense for us. You can start doing that work while Neuralink is still private.

Watch the presentation now, and see how I approach the next step.

Remember, the creative trader wins…

Jonathan Rose

Founder, Masters in Trading

P.S. Jonathan has given you two companies to investigate and explained why their connections to this developing field are different. That willingness to work through the details is one reason I encourage you to follow him. His $10K to $100K Challenge took place yesterday, but there’s still time to join!

Watch the presentation here to see how he finds opportunities, plans his trades, and manages risk.

The post Elon Musk’s Brain-Tech Push Has Me Watching These 2 Small Stocks appeared first on InvestorPlace.

Into the companies powering the artificial intelligence boom? Businesses using AI to transform their industries? Or a series of smaller, more aggressive trades?

In the first episode of The Investor Place, InvestorPlace’s new investing podcast, host Crystal Navellier puts that question to Louis Navellier, Eric Fry and Jonathan Rose.

Their answers take the conversation from AI chips and drug development to unusual options activity. Each expert names specific stocks he’s watching and explains how he would put that hypothetical $10,000 to work.

And when Crystal asks whether they’d rather hold cash or stocks, their differences become even clearer.

Click the image below to watch the debut episode of The Investor Place on YouTube.

Where Three Experts Would Invest $10,000

Louis Navellier: Follow the Earnings

Louis starts with the numbers. He looks for companies with dominant market positions, strong sales and earnings growth, expanding profit margins and growing order backlogs. Those backlogs help him judge whether demand can support the business over the next several quarters.

For his $10,000 portfolio, he chooses three companies tied to AI chips, memory and power. He explains how he would divide the money among them—and why he remains enthusiastic about the AI infrastructure boom.

Eric Fry: Look for AI’s Next Phase

Eric is looking closely at the next phase of AI investing: the companies applying the technology. He sees particular promise in biopharma and medical technology, where AI could help improve drug development and other healthcare applications.

He shares three stock ideas, including one that gives investors exposure to drug-development efforts across multiple companies. Louis pushes back on another of Eric’s picks, giving viewers a look at how two experienced stock pickers can reach different conclusions about the same company.

Jonathan Rose: Watch the Options Market

Jonathan takes a more aggressive approach. He watches unusual options activity for clues about where big money may be moving, then looks for ways to participate. For the hypothetical challenge, he describes dividing $10,000 among 10 positions, with $1,000 committed to each.

He names four candidates across copper, cybersecurity, space technology and AI in healthcare, and discusses using options to pursue larger potential gains. He also makes the risk clear: an individual position could lose the full amount invested.

Cash or Stocks? Here’s Where They Disagree

Picking investments is only part of the discussion. How quickly should you put fresh money into the market?

Louis favors being fully invested, pointing to earnings strength and seasonal trends. Eric sees reasons for caution and patience with new money. Jonathan favors keeping some cash available to buy potential pullbacks, even while expressing a bullish longer-term outlook.

Eric and Jonathan also raise concerns about rising bond yields and the different signals coming from small-cap and large-cap stocks. They explain why those risks deserve attention alongside the opportunities they see.

The episode closes with advice for investors putting their first $10,000 to work. Eric’s message is especially practical: start slowly enough to learn how you react when your own money is on the line.

For the full stock picks, Louis’s exact allocation and the reasoning behind all three approaches, watch the full conversation on YouTube.

Learn More About This Episode’s Experts

Get to know Louis Navellier, Eric Fry and Jonathan Rose—and explore their investing strategies, free content and premium research services.

Louis Navellier: Meet the down-to-earth investor behind the candid market commentary—and explore the stock-picking strategies he’s honed over more than four decades.
Sign up for his free Market360 e-letter here.

Eric Fry: From AI to commodities, uncover the global shifts—and overlooked companies—at the heart of his search for the next big investment opportunity.

Jonathan Rose: See how a former options market maker tracks unusual options activity and pricing gaps to turn market signals into trade ideas.
Join Jonathan’s free Masters in Trading class here.

The post Where to Invest $10,000: 3 Experts Share Their Next Moves appeared first on InvestorPlace.

I’ve been tracking that supply chain all year, from the rare-earth materials in a robot’s motors to the data centers and optical connections that let AI computing actually scale.

Today, I’m showing you how I work backward from Tesla’s Cybercab to find the businesses most investors overlook — the upstream materials plays and downstream computing-infrastructure names that don’t make the headlines, but still move on the same buildout.

And I want to let you in on a special event I hosted last night to help you consistently find an edge in the options market — The $10K to $100K Challenge.

I showed you everything my options playbook has to offer — the principles behind my trades, the charts, the tools, and the exact process I use to find an edge in any market.

Here’s the best part: you don’t need $10,000 to start. I showed you how to apply the same approach to smaller trades, including setups where you can keep the amount at risk below $500.

I’m keeping the full replay up for a limited time.I encourage you to check out the full replay right here.

And read on for those four AI stock picks I’m tracking right now…

On January 10, 1901, a drilling crew near Beaumont, Texas, struck more oil than it could handle.

The well at Spindletop sent a column of crude more than 100 feet into the air. It kept flowing for nine days before the crew managed to cap it, at an estimated rate of 100,000 barrels a day.

That’s the scene everybody remembers. Oil shooting 100 feet in the air. Texas had struck it rich.

But somebody still had to figure out what to do with all that oil.

One business that emerged from the boom, the Texas Fuel Co., bought and transported crude from Spindletop. The enterprise that became Texaco – now a subsidiary of Chevron Corp. (CVX) – expanded into pipelines and built a refinery at Port Arthur.

The discovery had created business well beyond the drilling site. There was money to be made getting the oil somewhere and turning it into something customers could use.

Today, energy industry investors have familiar names for those businesses. Exploration and production are upstream. Transportation and storage are midstream. Refining and selling finished products are downstream.

You can follow the same barrel of oil through several businesses and find different investments along the way.

I’ve been thinking about that as another “gusher” in Texas attracts investors’ attention.

On September 3, Tesla Inc. (TSLA) launched its Cybercab in Austin: a two-seat robotaxi without a steering wheel or pedals. Elon Musk wants passengers to climb in, choose a destination, and let the car do the driving.

It’s easy to see that and think, “I should just buy TSLA.”

Fair point. But I want to work backward from the car.

What goes into its motors? What computing capacity is needed to develop the AI? What equipment moves information between those computers?

Every answer, both upstream and down, gives me another business to investigate.

Today, I’ll show you four stocks I’m tracking across that buildout, from materials used in motors and batteries to computing infrastructure. And I’ll explain what gets my attention before I turn an investment idea into a trade.

Follow the Supply Chain, Not the Headline

A robot needs motors before it can move. AI computing needs facilities, electricity, and connections that can handle enormous amounts of information.

But being important to a story doesn’t make a stock a good trade.

I want to know what’s happening with the stock, whether what I call “unusual trading activity” deserves investigation, and what could cause buyers to pay more. Then I decide how much I’m willing to risk.

Let’s start toward the materials end of the supply chain… upstream of that Cybercab. Before anyone can build the motors or batteries, somebody has to supply the materials that go into them.

MP Materials Corp. (MP) produces rare-earth materials and is expanding U.S. magnet manufacturing. Those powerful magnets are used in electric motors, including motors that make robots move.

Our history with MP shows why the entry matters, too.

On July 7, 2025, a brokerage downgrade had knocked the stock. I still liked the opportunity and recommended a bullish trade.

Three days later, MP announced a Pentagon partnership that included a $400 million investment in preferred stock to help expand the domestic rare-earth magnet supply chain.

The stock surged. I told members to take profits on that position.

At our recorded prices, a $205 position had an exit value of $1,300—a $1,095 profit before fees. Our record shows a 534.15% gain in three days.

That’s the specific trade’s return, not the stock’s move. Not every trade works like that. But that’s why the entry matters.

The Metals Company Inc. (TMC) offers a more speculative upstream materials idea.

It’s pursuing mineral-rich nodules on the ocean floor containing copper, nickel, cobalt, and manganese, metals used in electrification and batteries. Proposed production depends on permitting and successful commercialization.

MP has an operating materials business. TMC is pursuing a new source of supply.

That distinction matters. A great demand story doesn’t tell you whether a company can execute, or whether the stock is worth buying today.

Follow the Demand Into Computing

Farther downstream—where the materials become equipment and facilities that make AI computing possible—is IREN Ltd. (IREN), which operates data centers supporting Bitcoin mining and AI computing.AI developers need computing capacity. That requires facilities with power and specialized equipment, the kinds of capabilities IREN offers.

But here’s what brought us into one IREN trade.

In March, my scanner flagged a large bullish transaction. A buyer had committed nearly $920,000 to a position looking for a substantial move higher over the next couple of months.

That didn’t identify the buyer or guarantee they were right, but it gave me something to investigate.

Bitcoin remained important to IREN’s business, while AI computing offered another source of demand. I recommended a bullish trade.

Then the stock fell.

We adjusted the position during the pullback while maintaining bullish exposure. After the shares recovered, we adjusted again to lower our trade’s net cost.

By May 6, IREN was planning an acquisition to expand its AI cloud capabilities, and its stock had gained roughly 66% over the preceding month.

I told members to close the remaining position. Our trade record shows a 485.28% gain for the managed trade, calculated on its reduced cost basis after those adjustments.

The job was never to fall in love with the story. The job was to recognize when the market gave us what we were looking for and to get out.

Another downstream company supplying that computing infrastructure is POET Technologies Inc. (POET).

Adding computing power creates another problem: moving information between machines quickly and efficiently.

POET develops optical components that move data using light, designed for connections in AI computing clusters and large data centers.

Producing more oil creates demand for transportation. Adding computing capacity creates demand for better connections.

The businesses are different, but the question is useful: As the industry expands, what else has to expand with it?

From the Supply Chain to the Trade

These four companies serve different needs and they’re not interchangeable. This isn’t a Tesla supplier list.

It’s a way to investigate opportunities beyond the finished robotaxis and other physical AI machines.

With my strategy, I take the next step: examining unusual trading activity, researching what might be driving it, and choosing a specific trade with a defined amount at risk.

I just went live to explain that strategy during my free $10K to $100K Challenge presentation last night

You can click here to watch the full replay for a limited time.

You’ll learn how I look for signs of large investors positioning and turn those clues into trades.

And you don’t need $10,000 to begin learning either. I’ll also explain opportunities where the amount at risk can be less than $500.

At Spindletop, the gusher was the part that made the newspapers. But businesses developed around everything that happened after the oil came out of the ground.

When I watch a Cybercab drive itself, I want to look beyond the car in the same way and investigate who supplies what it takes to make that ride possible.

Remember, the creative trader wins,

Jonathan Rose

Founder, Masters in Trading

The post Beyond Tesla: 4 Stocks I’m Watching for the Next AI Trade appeared first on InvestorPlace.

During the 2002 season, Oakland Athletics General Manager Billy Beane challenged baseball’s conventional wisdom. Instead of relying on traditional stats like batting averages and home runs, Beane focused on players who consistently got on base – a skill other teams undervalued. By looking where others weren’t, he found talent at a fraction of the cost.

Something similar is happening in the stock market. In a market obsessed with AI stocks, investors are fixated on the companies building AI… while overlooking an industry already putting the technology to work in potentially transformative ways:

Biopharma.

That oversight is exactly what creates opportunity.

Behind the scenes, biopharma companies are putting AI to work in ways that could make drug development faster, cheaper, and more precise. But investors may not be giving these companies credit for the potential to turn AI-driven innovation into stronger growth and profits.

In today’s Smart Money, let’s explore the potential hiding here – and one pharma giant that could be a bargain hiding in plain sight.

Then, I’ll share where to find even more opportunities before the rest of the market catches on.

A Pharma Giant Embraces AI at a Discount

The company I’m talking about is no longer just a drug maker; it is becoming a digital-first biomedical company. The company now uses AI to help design and evaluate nearly every drug program it runs – both small-molecule medicines and most of its large-molecule projects.

The company calls this approach “Predict First.” Before a single physical experiment runs, AI models assess the likelihood that a candidate drug will work, fail, or cause downstream problems. Virtually all of its small-molecule programs now run through this AI forecasting step before synthesis begins, up from just 5% as recently as 2021.

The benefits of the company’s “Predict First” approach are already visible. It has cut the time from lead optimization to toxicology work by 20%. It is on track to take two to three years off the average clinical trial timeline – a major strategic advantage in a business where a single Phase III trial can cost anywhere from tens of millions of dollars to several hundred million.

The company – Bristol-Myers Squibb Co. (BMY) – has also recently expanded its three-year partnership with Nvidia Corp. (NVDA) to build the most powerful AI infrastructure owned by any single life sciences company. By deploying a Nvidia “SuperPOD” of DGX Vera Rubin NVL 72 systems, the new platform will deliver up to 10 times more computing power per unit of energy than its predecessor.

Once operational, Bristol-Myers hopes to accelerate research across oncology, cardiovascular disease, immunology, hematology, and neuroscience. That hardware upgrade complements the company’s new enterprise-wide strategic agreement with Anthropic. Where the Nvidia deal supplies raw compute, the Anthropic partnership supplies the reasoning layer sitting on top of it.

Specifically, Bristol-Myers will deploy Anthropic’s Claude Enterprise platform across its global operations – reaching more than 30,000 employees. The agentic AI capabilities of this platform can take multistep actions, rather than just answer questions, across three priorities:

The company’s second-quarter 2026 results demonstrate early signs of progress.

Revenue rose 6% year over year to $13 billion, while adjusted EPS jumped 40% to $2.04. Its Growth Portfolio — newer drugs replacing aging blockbusters — delivered another strong quarter, with sales up 14%.

Bristol-Myers has several potential growth drivers, yet its stock trades at just 10 times estimated earnings, as the chart below shows.

Last October, its price-to-earnings (P/E) ratio hit a record-low discount of 75% to the S&P 500 – the widest in at least 35 years. The gap has narrowed since then, but BMY still trades at a 65% discount, meaning investors pay far less for each dollar of its earnings than they do for the average S&P 500 company.

In other words, BMY continues to trade as though the company’s robust “Growth Portfolio” and promising AI initiatives barely exist.

Pharma’s Potential Comeback

Bristol-Myers’ valuation is part of a broader disconnect across the pharmaceutical industry – one I highlighted last November in Fry’s Investment Report:

Valuations across the pharma sector have tumbled to record lows relative to the S&P 500. You’d have to go back more than 30 years to find valuations this depressed.

Since the day I highlighted this remarkable anomaly, the epic valuation gap between the pharma sector and the overall market has started to close. If the past is prologue, pharma stocks could be on the cusp of delivering surprisingly strong returns.

Back in 1994, when BMY shares fell to a similarly extreme discount, its stock tripled within three years. Then, they continued climbing to advance 500% within five years, which was more than double the S&P 500’s gain over the same stretch.

In hindsight, that opportunity should have been obvious. Bristol-Myers was entering a new growth phase and was producing profit margins that were triple those of the S&P 500.

Today, the fundamentals of the pharma sector look even stronger than they did at that 1994 trough. Revenues and net profit are trending sharply higher, as operating margins approach a two-decade high.

Now, none of these virtues mean investors will rekindle a love affair with pharma stocks anytime soon, but they probably should.

The Overlooked 1,076% Pharma Play

I believe that some of the best investment opportunities will come out of the biopharma and medtech industries. And my colleague Jonathan Rose agrees. In fact, biopharma is one of his favorite industries to trade.

That’s because it fits his strategy: finding opportunities where the market isn’t looking. Like Billy Beane, Jonathan looks for value hiding in plain sight. And the market’s fixation on AI infrastructure stocks may be causing investors to overlook pharmaceutical and medtech companies already putting AI to work.

He also looks for disconnects between a stock’s price and its underlying fundamentals. Pharma stocks, as we’ve discussed, remain relatively inexpensive despite the potential for AI adoption to improve drug discovery, productivity and profitability.

That disconnect is the opportunity in the sector – and it’s why I recommended Bristol-Myers to my Fry’s Investment Report subscribers. I continue to view the company as a “Strong Buy.”

While I remain bullish on the fundamental case for pharma stocks, Jonathan took a different approach with BMY. By using a short-term trade, he achieved a 1,076% gain on the company in less than three months.

Jonathan uses an AI-powered system to spot unusual trading activity that may signal an impending move in a stock. He then uses those signals to capitalize on sharp price movements and issue short-term trades, without needing to predict the market’s next big winner.

Jonathan detailed how he uses unusual trading activity to identify potential big moves in his latest special broadcast, released just last night.

As he often says, “The creative trader wins.” And sometimes, the most creative trade is the one nobody else sees coming. Play ball!

Regards,

Eric Fry

P.S. In that new broadcast, Jonathan has an ambitious goal: to show folks how they can turn $10,000 into $100,000 using his trading strategy. Jonathan brings decades of professional trading experience — and a knack for making the lessons understandable. Go here to see how he finds opportunities, plans his trades, and decides what he’s willing to risk.

The post The AI Bargain Hiding in Big Pharma appeared first on InvestorPlace.

Homeownership belonged to people who already had money. Then banks learned they could treat a house itself as collateral, lend against it, and collect over 30 years. And suddenly, the biggest asset most families would ever own became financeable. The housing market we know today isn’t a product of lumber and land but of lending.

Wall Street is now running the same play on a new asset: AI hardware.

SpaceX (SPCX) is reportedly in talks for a $40 billion debt package to buy Nvidia (NVDA) chips – roughly $10 billion in bank loans and $30 billion in investment-grade debt. The discussions are preliminary and could still fall apart. But the sheer size of the ask rattled credit markets: SpaceX’s credit-default-swap spreads and bond risk premiums jumped on the news.

But SpaceX is one borrower in what’s quickly becoming a crowd. Broadcom (AVGO) is supposedly lining up more than $50 billion – with Apollo and Blackstone among the prospective lenders – to finance OpenAI’s custom chip buildout. Oracle (ORCL) is seeking outside capital for chip purchases. And CoreWeave (CRWV) – which had piled up about $52 billion in debt and lease obligations by June – is pursuing investment-grade ratings specifically so it can tap what one of its founders described as the nearly ‘unlimited’ capital held by life insurers.

The AI boom has outgrown the cash sitting on Big Tech’s balance sheets. So the financial system is building a new market around it.

That could matter almost as much as the chips themselves.

The AI Buildout Is Outgrowing the Cash-Funded Model

Every transformative buildout in history has hit the same wall: eventually, the project grows bigger than its builders’ wallets. What carries it over, every time, is fresh financial plumbing.

Railroads didn’t blanket the continent on railroad-company profits; they ran on railroad bonds. Homeownership spread on mortgages, not savings. Power plants, pipelines, and toll roads got their own mechanism – project finance – where lenders underwrite the asset and its contracted cash flows rather than the company that owns it.

AI compute is crossing that threshold right now. GPU-backed loans. Special-purpose vehicles. Residual-value guarantees. Private-credit packages. Insurer-funded, investment-grade debt. Piece by piece, Wall Street is learning to value the hardware, underwrite the contracts behind it, and finance the facilities around it.

Once Wall Street figures out how to lend against something, a whole lot more of that something gets built.

How AI Infrastructure Financing Turns Debt Into Purchase Orders

Underneath all that financial engineering, the money moves in a loop:

• Banks, insurers, and private-credit funds put up the capital.
• The operator – a SpaceX, a CoreWeave, an Oracle – buys chips and builds capacity.
• Long-term customer contracts for that capacity support the debt.
• And the suppliers – Nvidia, Broadcom, the memory makers, the networking vendors, the power-equipment companies – get paid up front, while the operator spends years working to earn an adequate return.

That fourth step is where the entire investment case lives: the borrowers carry the financing and utilization risk. The suppliers collect the orders first. 

I’ll be honest about the risk side of this. Debt converts flexible spending into fixed obligations, and those widening SpaceX credit spreads are the market pricing exactly that. If AI capacity ultimately fails to generate the cash flows these loans assume, the pain won’t stay contained to the borrowers – it would eventually reach suppliers through weaker future orders. 

But it’s a future risk, and the demand keeps pushing it further out. CoreWeave says most of its capacity is already sold through 2027. The contracts supporting these debt packages are being signed by customers who can’t get enough compute today. For now – and likely for years – the machine keeps converting borrowed money into purchase orders.

4 AI Infrastructure Stocks That Get Paid First

I’d keep the basket tight:

Apollo, Blackstone, KKR, and other alternative-asset managers are deeply involved in this ecosystem, too. But suppliers get paid first, in cash, regardless of how any individual loan performs.

The Bottom Line: Wall Street Is Becoming Part of the AI Supply Chain

A year ago, the question hanging over the AI trade was whether the spending could continue once the hyperscalers’ cash got tight. 

We’re now learning that the buildout no longer has to rely on corporate cash alone. Wall Street is building the mortgage market that lets the buildout keep compounding, with insurers, banks, and private credit all learning to lend against chips and contracts.

Railroads got bonds. Houses got mortgages. AI is getting its own financing machinery – and once it exists, it doesn’t finance small plans.

That’s exactly why I keep pointing readers toward XPANSE.

Once the financing ecosystem exists, the capital goes hunting for the biggest project it can fund. I believe that project is the one Elon Musk is assembling across AI, robotics, energy, and space – what I call XPANSE. And the window where you can position before those dollars start moving is exactly the window we’re in now.

My free briefing gives you the full thesis, the three steps to take now, and the name and ticker of my favorite stock to play it.

In every lending boom, the safest seat belongs to whoever gets paid in cash, up front. These are the companies in that seat.

Watch the briefing and learn all about that free pick now.

The post What SpaceX’s $40 Billion Nvidia Chip Plan Says About the AI Boom appeared first on InvestorPlace.

This morning’s Consumer Price Index (CPI) report put an October rate hike squarely back on the table…

Headline CPI rose 0.6% in September, putting annual inflation at 3.7%. That’s up from 3.4% in August, and a tick above the 3.6% economists expected.

Core CPI, which strips out volatile food and energy prices, climbed 0.3% for the month and 2.6% over the past year. Both readings came in above forecasts of 0.2% and 2.5%.

Energy remains the main culprit. Gasoline prices jumped 9.1% in September alone, accounting for about half of the headline increase. Thanks to the conflict in Iran, gas is now up 34% over the past year.

But the more concerning takeaway is that inflation is spreading beyond the gas pump. Shelter, vehicle, and apparel prices all moved higher. And with the AI build-out driving demand for chips and hardware, the cost of computers and related items is up nearly 10% over the past year.

Meanwhile, wages are not keeping up – they grew just 3% over the past year.

So, what does the Fed do now?

Last month, the Federal Reserve raised rates for the first time in more than three years, lifting its target range to 3.75%-4%. FOMC officials had signaled they’d likely sit tight at their meeting in two weeks before hiking again in December.

This report puts that timeline in question.

According to CME Group’s FedWatch Tool, traders yesterday saw a 22% chance of an October hike. As I write on Wednesday, after the CPI data, those odds have more than doubled to 49%. It’s essentially a coin flip.

Source: CME Group

Looking further out, traders now see a 94% chance of at least one more hike by year-end. And the odds of two hikes, which would push the target range to 4.25%-4.5%, have more than doubled from 19% to 44%.

Turning to the market’s reaction, Wall Street isn’t thrilled.

As I write, all three major indexes are in the red, with the Nasdaq leading the losses, off more than 1%.

Over in the bond market, as you’d expect, the 10-year Treasury yield is jumping. It’s up to 5.27%. Meanwhile, gold and metals are selling off.

Bottom line: this morning didn’t bring the data that the bulls wanted. In the meantime, a market like this rewards knowing exactly where big money is moving. And that dovetails with a reminder about this evening…

Tonight at 8 p.m. Eastern, Jonathan Rose goes live

In just a few hours, veteran trader Jonathan Rose will sit down for his free $10K to $100K Challenge event.

Starting at 8 p.m. Eastern, Jonathan will walk through everything behind his approach. He’ll cover the principles that guide his trades, the charts and tools he relies on, and the process he uses to look for an edge in the market. It’s a system he believes could help traders turn $10,000 into $100,000 in one year.

You still have time to join. Just click here to reserve your free seat, and we’ll see you in a few hours.

In the meantime, let’s look at a corner of the market where Jonathan sees money moving right now. As you’ll see, this isn’t just a short-term trading idea. It’s a sector that could anchor your portfolio for years to come.

On a selloff day like today, it’s helpful to focus on where the money is flowing now – and likely to flow for years to come

There’s one answer: cybersecurity.

This was the focus of Jonathan’s free Masters in Trading LIVE episode yesterday. Here he is, setting it up:

AI isn’t just changing how we work and interact with each other. It’s changing how hackers attack us.

To his point, for decades, a sophisticated cyberattack required a skilled team, plenty of time, and a lot of painstaking manual work. AI is collapsing all three.

Jonathan highlighted a campaign detailed by Anthropic in which AI agents handled 80% to 90% of the tactical work, from finding vulnerabilities to stealing passwords. The human attackers mostly had to point the agents at a target and let them run.

And the data show this is no isolated case:

• According to IBM’s 2026 Cost of a Data Breach Report, one in four malicious breaches is now AI-enabled, a 56% jump in a single year. Those AI-enabled breaches cost companies about $6 million each, roughly $1 million more than the average breach.
• For the first time in its history, the FBI’s annual Internet Crime Report included a section dedicated to AI. It tied more than 22,000 complaints and nearly $893 million in losses to AI-enabled schemes last year. Overall reported cybercrime losses hit a record $20.9 billion, up 26% from the year before.
• CrowdStrike (CRWD) reports that AI-enabled attacks jumped 89% year over year. The average “breakout time” (how long it takes an attacker to move from the first compromised computer deeper into a company’s network) is now 29 minutes. The fastest CrowdStrike recorded took just 27 seconds.

Twenty-seven seconds is faster than most security teams can open an alert, let alone respond to one.

Ultimately, the very speed and intelligence that make AI a powerful tool for innovation also make it a potent weapon for bad actors.

The only answer is to fight AI with AI

So, what does a company do when attackers have AI on their side?

It fights back with its own AI.

We got a preview of that future in April when Anthropic revealed that its unreleased Claude Mythos Preview model had uncovered thousands of previously unknown “zero-day” vulnerabilities across every major operating system and web browser.

To make sure we’re all on the same page, a zero-day is a security flaw that the software’s developers don’t know exists, leaving them zero days to fix it before attackers can strike. One of those flaws had sat undetected for 27 years in OpenBSD, an operating system famous for its security.

Anthropic chose not to release the model publicly. Instead, it gave access to a coalition of tech and security leaders, including CrowdStrike and Palo Alto Networks Inc. (PANW), so they could patch the holes before bad actors found them.

That’s the template for what comes next: an arms race in which defenders need frontier AI just to keep pace with attackers who have it too.

But arms races are expensive. Gartner projects worldwide information security spending will reach nearly $250 billion this year and climb to roughly $373 billion by 2030.

Investors would be wise to position themselves in the companies on the receiving end of those billions. And that brings us back to Jonathan and why he’s watching this space so closely:

Even as the AI trade gets crowded, the security infrastructure behind it is one segment markets haven’t fully woken up to yet.

That’s where the real opportunity lives right now.

In yesterday’s episode, Jonathan profiled five names, including Palo Alto, CrowdStrike, and Okta Inc. (OKTA), and explained why one stock stands above the rest.

You can watch the full breakdown right here.

But this isn’t just a shorter-term trade – it’s also a longer-term “Inevitable”

Jonathan’s approach can help you profit from cybersecurity over a matter of days or weeks. But here at the Digest, we believe the sector also deserves a place in your portfolio for a much longer stretch. We mean the kind of position you buy and largely forget about for years.

To explain why, let’s revisit a concept that can help you build wealth in stocks more than almost any other. We at InvestorPlace call it “Inevitables.”

The term comes from Warren Buffett, who used it for businesses with such enormous competitive advantages that they dominate their industries for decades. Here’s Buffett in his 1996 letter to Berkshire Hathaway shareholders:

Companies such as Coca-Cola and Gillette might well be labeled “The Inevitables.” Forecasters may differ a bit in their predictions of exactly how much soft drink or shaving-equipment business these companies will be doing in ten or twenty years…

In the end, however, no sensible observer – not even these companies’ most vigorous competitors, assuming they are assessing the matter honestly – questions that Coke and Gillette will dominate their fields worldwide for an investment lifetime.

In simple terms, Inevitables are the market leaders in sectors that will be in demand for decades to come.

But there’s a twist…

Inevitables don’t have to be individual stocks. The concept also applies to technologies, trends, and cultural shifts so powerful that massive growth becomes, well, inevitable.

With that context, look back at everything we just covered…

Attackers are getting faster and cheaper to deploy. AI-enabled breaches are becoming more common and more costly. And defenders have no choice but to spend heavily on AI of their own.

None of that reverses next quarter or next year. As long as AI keeps advancing, the need to defend against it advances right alongside it.

That’s what an Inevitable looks like.

So, how do we invest?

You can start with the names that Jonathan highlighted in yesterday’s episode. But if you want a simple one-click solution, consider a broad ETF like the Amplify Cybersecurity ETF (HACK). It holds many of the top names in cybersecurity – Cisco Systems Inc. (CSCO), Cloudflare Inc. (NET), Fortinet Inc. (FTNT), Zscaler Inc. (ZS), and F5 Inc. (FFIV), to name a handful.

As you can see below, HACK is up about 70% over the last six months, more than six times the S&P 500’s 11% return.

Now, notice where that chart begins…

On April 14 – the same day that the Digest covered the cybersecurity selloff that followed the Mythos news.

Palo Alto fell 11%, CrowdStrike dropped 12%, and Zscaler shed 16% in a matter of days. Back then, the fear was that AI would make traditional cybersecurity obsolete. Since then, the market has reached a very different verdict…

AI isn’t replacing cybersecurity. It’s making it essential.

Two ways to play one Inevitable

After a 70% run in six months, it’s fair to ask whether you’ve already missed it.

If you’re investing for the long haul, the answer comes back to the Inevitables idea. When demand looks set to grow for a decade or more, the exact entry point matters far less than owning the trend.

Many long-term investors scale in gradually, adding to positions on pullbacks rather than buying all at once.

And there have been pullbacks. Look at the chart again, and you’ll see that HACK’s climb has been anything but a straight line. The ETF gave back weeks of gains in June, again in late July and again in late August before pushing to new highs. And it’s selling off today as I write.

For a buy-and-hold investor, those dips are noise. But for a trader, they’re opportunity…

Spotting where big money is positioning before the next move is exactly what Jonathan does – which brings us back to the trading process that he’ll walk through tonight at 8 p.m. Eastern in his free $10K to $100K Challenge. Click here to join us in a few hours.

Wrapping up, there are two ways to play this Inevitable – own it for the long run or trade the swings along the way. Either way, we believe this trend is going much, much higher in the years to come.

Have a good evening,

Jeff Remsburg

(Disclosure: I own HACK)

The post The Odds of a Rate Hike Just Doubled appeared first on InvestorPlace.

Today, my colleague Jonathan Rose brings another useful perspective to that discussion: how a trader evaluates these opportunities after investors start bidding up their shares. His ability to spot unusual trading activity—and turn it into a practical trading idea—is why I want you to follow his work.

Below, he explains what government backing can mean for your next trade.

He also shares details about his free $10K to $100K Challenge, happening tonight at 8 p.m. Eastern, and explains how it can help you approach trades like these. Sign up here to learn how he evaluates both profit potential and risk.

Hey, guys.

In September 2008, Washington stepped in to rescue Fannie Mae and Freddie Mac.

These were enormous companies with an enormous job. Millions of American mortgages ran through the system they helped finance. The government couldn’t let that collapse.

But here’s the distinction that mattered — a lot — to anyone who owned their shares.

Washington was protecting the mortgage market. It was protecting holders of the companies’ debt. Existing shareholders? They bore losses. Common shareholders were further back in line to recover their money.

Washington was protecting a vital economic function. That didn’t mean it was protecting the price you paid for the stock.

Investors today call this kind of support a “government put” — the idea that the White House’s backing puts a floor under certain stocks. It’s a useful concept. But like all useful concepts, it can be taken too far.

Keep that in mind as you look at today’s Washington-backed opportunities. Domestic chipmaking, rare-earth production, artificial intelligence — all the industries the administration has decided are essential to America’s future.

These companies are in a completely different situation from Fannie and Freddie. But the same question applies: What, exactly, is the government protecting — and how much are you paying for it?

Answer those two things honestly, and you’ll make better trades.

Louis has been explaining why government policy can support certain businesses. I want to take that one step further and show you how I actually look at their stocks. Because a company can have a powerful tailwind and still be a bad trade at the wrong price.

And a stock that looks expensive today can become a really good opportunity after it pulls back.

In this piece I’m going to show you how I think about that, including two names I’m bullish on right now, two I’m leaving alone, and the three questions I ask before I put any government-backed trade on.

What Washington’s Support Is Actually Worth

Think about buying a house.

You find a property you like. A major employer is moving nearby, and the town is fixing the roads. So you think demand could rise.

Those are all good reasons to take a closer look.

But you still check what similar properties have actually sold for nearby. You still inspect the property. And you still ask whether the seller has already priced in every improvement you’re excited about.

Same thing here.

A federal investment, a contract, a favorable policy — any of those can genuinely improve a company’s prospects. Once that news is public, though, investors pile in fast. The shares jump. And a lot of the good news is already in the price.

I call that the Washington premium.

It’s not a precise number. It’s just a way of thinking about how much of a stock’s appeal depends on what investors are expecting from the White House — not from the business itself.

And the support comes in different forms. It matters which kind you’re looking at.

Sometimes Washington is an investor. Intel Corp. (INTC) reached an agreement with the Trump administration for an $8.9 billion investment — a 9.9% passive stake, no board representation. That’s a serious commitment to domestic semiconductor manufacturing. It also leaves every normal business question on the table. Can Intel execute? How competitive are their products? What do their earnings look like? What price actually makes sense for the shares?

Sometimes Washington supports a company’s production economics. MP Materials Corp.’s (MP) agreement with the Pentagon included a 10-year price floor on its neodymium-praseodymium products, plus financing and purchase commitments tied to expanding domestic magnet production. That makes the business more dependable. But a floor under the price of a product is not the same thing as a floor under the price of the stock. If investors overpay, the stock can still go down.

And sometimes Washington controls who a company can sell to. That’s the export policy question for Nvidia Corp. (NVDA) and Advanced Micro Devices Inc. (AMD). You can be completely bullish on long-term demand for computing power and still recognize that a single federal policy headline can swing these stocks in the short term.

That’s why I don’t throw all these names into one basket labeled “Trump stocks.” Their businesses are different and their government relationships are different, so they deserve to be looked at separately.

So, here’s where I land: bullish on Microsoft Corp. (MSFT) and Nvidia and bearish on Intel and Oracle Corp. (ORCL). Those are separate judgments about separate opportunities, not one big trade on Washington.

Three Questions I Ask Before Getting Involved

First: What does the government commitment actually cover?

A signed purchase agreement is very different from a politician making encouraging comments. An actual investment is different from a potential investment. And even a big commitment may only support one slice of a company’s overall business. I want to know what’s real before I start deciding what it’s worth.

Second: How much good news is already in the stock?

If a company gets meaningful support and the shares immediately surge 40%, buying afterward means paying the new price. You don’t get the earlier entry just because you correctly understood the news first. This is where patience matters. I’d rather put a name on my watchlist and wait for a setup I like than chase it because everyone’s suddenly talking about it.

Third: What’s my plan if expectations change?

With the November 3 midterm elections approaching, investors are going to start thinking about how a different political balance might affect Washington’s priorities. That doesn’t mean existing agreements disappear. But a stock can absolutely move because investors become less confident about future support — about additional contracts, about the pace of a project. The underlying business stays intact while the premium investors are willing to pay just leaks out. Before I enter a trade, I decide how much I’m willing to risk and what would make me reconsider. Then I go look at the trading itself for confirmation.

My approach centers on unusual trading activity — big, concentrated trades that tell me whether serious money is building a position. That activity gives me something to dig into alongside the news, the company, and the price.

It doesn’t make every trade a winner, but it definitely helps me focus my attention on the right places.

One MP Materials options trade on our record offered a potential gain of 534% in three days. That’s an options result — not a 534% move in MP’s shares — and an individual trader’s outcome depended on their entry and exit. But it shows why I spend so much time thinking about how to structure a trade and when to make it, not just whether the company is good.

You could identify an attractive company and buy the stock. You could find an options opportunity with a smaller initial outlay. Or you could decide the opportunity is already too expensive and wait. The decision depends on the price, the timing, and the risk you’re willing to take.

That’s the work. And it’s what I want to help you understand.

You can see how I approach it every day by joining me at Masters in Trading LIVE — free on YouTube at 11 a.m. Eastern every day the market is open. I walk through what I’m watching, explain the activity that caught my attention, and tell you why something interests me — or why I’m leaving it alone.

And to give your portfolio an extra boost, I’d like to invite you to take my $10K to $100K Challenge. You don’t need $10,000 or years of trading experience to attend. Tonight at 8 p.m., I’ll explain more about how I spot unusual trading activity and use it to identify opportunities. I’ll also show how my approach can work with trades that risk less than $500.

If you’d like to learn from my approachable process, reserve your spot here.

Washington’s involvement can absolutely create valuable opportunities. Understanding the “government put” is part of understanding these businesses. But then comes the next decision: what to pay, how to participate, how much to risk.

Remember 2008 and what happened to Fannie and Freddie. Government support has a specific purpose. Find out what that purpose is and figure out what it means for the business. And then make sure the trade makes sense at the price in front of you, not the price it was before everyone else figured it out.

Remember, the creative trader wins.

Jonathan Rose

Founder, Masters in Trading

P.S. My colleague Jonathan Rose has an ambitious goal: Show folks how they could turn $10,000 into $100,000 using his trading strategy. Tonight at 8 p.m. Eastern, he’ll explain his approach during the free $10K to $100K Challenge. Jonathan brings decades of professional trading experience — and a knack for making the lessons understandable. Sign up here to see how he finds opportunities, plans his trades, and decides what he’s willing to risk.

The post Get In on Washington’s Winners – On Your Terms appeared first on InvestorPlace.

Today, I’m showing you how a trader evaluates these opportunities after investors start bidding up their shares – and why that perspective could hand you the greatest edge in a volatile market.

And tonight, I’m going live to show you how to consistently discover an edge in the options market with my $10K to $100K Challenge.

Tonight, you’ll learn everything my approach has to offer — the principles behind our trades, the charts, the tools, and the exact process I use to find an edge in the market.

Here’s the best part: you don’t need $10,000 to start. I’ll show you how to apply the same approach to smaller trades, including setups where you can keep the amount at risk below $500.

It’s all in tonight’s special presentation. Just click here to sign up for my free webinar.

In September 2008, Washington stepped in to rescue Fannie Mae and Freddie Mac.

These were enormous companies with an enormous job. Millions of American mortgages ran through the system they helped finance. The government couldn’t let that collapse.

But here’s the distinction that mattered — a lot — to anyone who owned their shares.

Washington was protecting the mortgage market. It was protecting holders of the companies’ debt. Existing shareholders? They bore losses. Common shareholders were further back in line to recover their money.

Washington was protecting a vital economic function. That didn’t mean it was protecting the price you paid for the stock.

Investors today call this kind of support a “government put” — the idea that the White House’s backing puts a floor under certain stocks. It’s a useful concept. But like all useful concepts, it can be taken too far.

Keep that in mind as you look at today’s Washington-backed opportunities. Domestic chipmaking, rare-earth production, artificial intelligence — all the industries the administration has decided are essential to America’s future.

These companies are in a completely different situation from Fannie and Freddie. But the same question applies: What, exactly, is the government protecting — and how much are you paying for it?

Answer those two things honestly, and you’ll make better trades.

Louis has been explaining why government policy can support certain businesses. I want to take that one step further and show you how I actually look at their stocks. Because a company can have a powerful tailwind and still be a bad trade at the wrong price.

And a stock that looks expensive today can become a really good opportunity after it pulls back.

In this piece I’m going to show you how I think about that, including two names I’m bullish on right now, two I’m leaving alone, and the three questions I ask before I put any government-backed trade on.

What Washington’s Support Is Actually Worth

Think about buying a house.

You find a property you like. A major employer is moving nearby, and the town is fixing the roads. So you think demand could rise.

Those are all good reasons to take a closer look.

But you still check what similar properties have actually sold for nearby. You still inspect the property. And you still ask whether the seller has already priced in every improvement you’re excited about.

Same thing here.

A federal investment, a contract, a favorable policy — any of those can genuinely improve a company’s prospects. Once that news is public, though, investors pile in fast. The shares jump. And a lot of the good news is already in the price.

I call that the Washington premium.

It’s not a precise number. It’s just a way of thinking about how much of a stock’s appeal depends on what investors are expecting from the White House — not from the business itself.

And the support comes in different forms. It matters which kind you’re looking at.

Sometimes Washington is an investor. Intel Corp. (INTC) reached an agreement with the Trump administration for an $8.9 billion investment — a 9.9% passive stake, no board representation. That’s a serious commitment to domestic semiconductor manufacturing. It also leaves every normal business question on the table. Can Intel execute? How competitive are their products? What do their earnings look like? What price actually makes sense for the shares?

Sometimes Washington supports a company’s production economics. MP Materials Corp.’s (MP) agreement with the Pentagon included a 10-year price floor on its neodymium-praseodymium products, plus financing and purchase commitments tied to expanding domestic magnet production. That makes the business more dependable. But a floor under the price of a product is not the same thing as a floor under the price of the stock. If investors overpay, the stock can still go down.

And sometimes Washington controls who a company can sell to. That’s the export policy question for Nvidia Corp. (NVDA) and Advanced Micro Devices Inc. (AMD). You can be completely bullish on long-term demand for computing power and still recognize that a single federal policy headline can swing these stocks in the short term.

That’s why I don’t throw all these names into one basket labeled “Trump stocks.” Their businesses are different and their government relationships are different, so they deserve to be looked at separately.

So, here’s where I land: bullish on Microsoft Corp. (MSFT) and Nvidia and bearish on Intel and Oracle Corp. (ORCL). Those are separate judgments about separate opportunities, not one big trade on Washington.

Three Questions I Ask Before Getting Involved

First: What does the government commitment actually cover?

A signed purchase agreement is very different from a politician making encouraging comments. An actual investment is different from a potential investment. And even a big commitment may only support one slice of a company’s overall business. I want to know what’s real before I start deciding what it’s worth.

Second: How much good news is already in the stock?

If a company gets meaningful support and the shares immediately surge 40%, buying afterward means paying the new price. You don’t get the earlier entry just because you correctly understood the news first. This is where patience matters. I’d rather put a name on my watchlist and wait for a setup I like than chase it because everyone’s suddenly talking about it.

Third: What’s my plan if expectations change?

With the November 3 midterm elections approaching, investors are going to start thinking about how a different political balance might affect Washington’s priorities. That doesn’t mean existing agreements disappear. But a stock can absolutely move because investors become less confident about future support — about additional contracts, about the pace of a project. The underlying business stays intact while the premium investors are willing to pay just leaks out. Before I enter a trade, I decide how much I’m willing to risk and what would make me reconsider. Then I go look at the trading itself for confirmation.

My approach centers on unusual trading activity — big, concentrated trades that tell me whether serious money is building a position. That activity gives me something to dig into alongside the news, the company, and the price.

It doesn’t make every trade a winner, but it definitely helps me focus my attention on the right places.

One MP Materials options trade on our record offered a potential gain of 534% in three days. That’s an options result — not a 534% move in MP’s shares — and an individual trader’s outcome depended on their entry and exit. But it shows why I spend so much time thinking about how to structure a trade and when to make it, not just whether the company is good.

You could identify an attractive company and buy the stock. You could find an options opportunity with a smaller initial outlay. Or you could decide the opportunity is already too expensive and wait. The decision depends on the price, the timing, and the risk you’re willing to take.

That’s the work. And it’s what I want to help you understand.

You can see how I approach it every day by joining me at Masters in Trading LIVE — free on YouTube at 11 a.m. Eastern every day the market is open. I walk through what I’m watching, explain the activity that’s caught my attention, and tell you why something interests me — or why I’m leaving it alone.

Sign up here, and we’ll email you the link each market day, along with additional columns and research from me.

And if you’re interested in diving deeper into the system I’ve built over 28 years in the options market…

Tonight at 8PM, I’m going live with the $10K to $100K Challenge.  It’s a special presentation that won’t just show you how to set up in the next wave of Trump stocks. I’m showing you the system I used to find those names in the first place and how you can apply it to over sector of the open market. And I’ll be revealing a simple strategy that could help you turn every $10,000 into $100,000.

One thing that will become abundantly clear tonight is I’m not one to make lofty or false promises. Instead, my success — and the success of my readers — is anchored by a simple strategy I perfected while working the options market over three decades. This strategy works in bull markets and bear markets…

And it doesn’t matter what’s happening with AI, interest rates, midterm elections, you name it. The same process underpins every trade I make.

Just click here to sign up for the full presentation.

Remember, the creative trader wins.

Jonathan Rose

Founder, Masters in Trading

The post Do This Before You Buy Another “Trump Stock”… appeared first on InvestorPlace.

A gigawatt of data-center capacity, according to Bloomberg Intelligence’s freshly revised modeling. The gigawatt didn’t change. What goes inside it did.

Bloomberg raised its 2027 global capacity forecast from 108 gigawatts to 119 – about a 10% bump. But its estimate of what that capacity will cost jumped from about $1 trillion to $1.7 trillion – a 70% leap. 

Every new gigawatt is being stuffed with more accelerators, more high-bandwidth memory, more storage, faster networking, and far heavier power and cooling equipment than the model assumed a year ago.

The original AI trade revolved around a handful of chip companies. Bloomberg’s new math highlights how that money spreads across the entire building.

Here’s where I think it flows next…

Why the AI Data Center Buildout Just Got 70% More Expensive

Bloomberg sees the global data-center market growing from roughly $630 billion in 2025 to $1.06 trillion in 2026, $1.74 trillion in 2027, and $2.8 trillion by 2030. 

Capacity climbs alongside it – 119 gigawatts in 2027 and 229 by 2030, up from a prior 2030 estimate of 189.

And the buyer base keeps widening. Hyperscalers started this boom, neoclouds followed, and now sovereign AI programs, governments, and large enterprises are building capacity of their own.

More buyers are chasing a more hardware-intensive buildout. Put those forces together, and Bloomberg’s 2027 spending estimate is roughly $700 billion higher than before. So, where does all that extra money go?

Across nearly every layer of the data center.

1. Compute: Nvidia Still Gets the Biggest Check

One category collects the largest check by far.

Bloomberg expects compute servers and GPUs to absorb roughly $1.1 trillion of the 2027 market – nearly two-thirds of the total.

Nvidia (NVDA) remains the clearest anchor for that spending. Its latest quarterly data-center revenue hit $89 billion, up 117% year over year, and the Vera Rubin platform is now ramping across the major cloud providers.

What’s driving the growth? Frontier models keep getting bigger. Reasoning systems spend more time on each request. Agents keep working long after the initial prompt, and more companies and countries are building AI at once. Every one of those trends consumes more compute.

Nvidia remains my core holding for this layer of the boom. But Bloomberg’s data shows the opportunity gets much bigger once you look past the processor.

2. Memory: Small Models, Giant Appetites

Included in Bloomberg’s model is the finding that might surprise you most: when it comes to high-bandwidth memory (HBM), small models aren’t small.

Under its modeled workloads, even a modest 7-billion-parameter model could require roughly 1.6 terabytes of high-bandwidth memory – surprisingly close to what far larger models need.

That’s because inference memory goes well beyond storing the model itself. The system needs working memory – the key-value cache – which balloons as context windows stretch and more users pile on simultaneously, plus headroom to run reliably. A compact model serving thousands of long-running agents can chew through enormous amounts of memory.

That makes Micron Technology (MU) one of my favorite plays here. It’s already shipping HBM4 for Vera Rubin, more than 75% of its fiscal 2027 output is committed, and customers are discussing allocations into 2028 and beyond. 

And every big usage trend – more users, longer conversations, agents that never log off – pulls on that same memory supply.

3. Storage: AI’s Quietest Spending Explosion

AI has to remember far more than most investors realize – training sets, model checkpoints, video and sensor data, agent logs, customer records, generated files, and everything needed to audit a system when something goes wrong.

Bloomberg sees total storage growing from roughly $125 billion in 2025 to $612 billion in 2030 – and the data-center slice rises much faster. Nearline hard drives and data-center flash were about $39 billion of spending in 2025; Bloomberg’s 2030 mix implies roughly $360 billion. That’s nearly a ninefold increase.

Seagate Technology (STX) shines in this category. Its high-density drives give hyperscalers an economical way to retain massive pools of training data and AI-generated content, and its latest HAMR platform is already qualified with major cloud customers. 

Sandisk (SNDK) is the faster, more aggressive flash angle. Hard drives preserve the data lake; flash serves whatever needs answers right now. The AI economy needs plenty of both.

4. Networking: More AI Chips Create More Traffic Between Them

An AI cluster can hold tens of thousands of processors. As clusters grow, networking content grows with them – and persistent agents turn that traffic from bursts into a constant flood. Custom accelerators add even more connections among CPUs, GPUs, memory, and storage.

That’s Marvell Technology’s (MRVL) sweet spot. It participates in custom silicon and supplies the high-speed optical and networking technology that moves information through these systems. A hyperscaler can design its own accelerator; but it still needs that chip wired to everything around it. Marvell is my preferred higher-growth networking play on that traffic.

5. Power and Cooling: The GPU Is Useless Without Electricity

AI racks pull extraordinary amounts of electricity into a tiny footprint and convert most of it into heat. That creates two immediate jobs: get enough power to the rack, and carry the heat away.

Vertiv Holdings (VRT) sells the equipment for both, spanning power distribution, backup, liquid cooling, thermal management, and modular infrastructure. And it’s expanding into microgrids and behind-the-meter power so data centers can make their own electricity instead of waiting in the grid’s years-long connection line. 

The old bottleneck was getting the GPU. The next one may be getting that GPU enough electricity to switch on. Vertiv is my favorite power-and-cooling stock for this phase.

6. Copper and the Grid: AI Spending Doesn’t Stop at the Data Center

A data center’s bill of materials doesn’t stop at its own walls. 

Bloomberg estimates direct data-center copper use could rise from roughly 390,000 metric tons in 2025 to about 1.3 million tons by decade’s end – and the generators, substations, transformers, and transmission lines feeding those campuses could require another 770,000 tons. Combined, that’s potentially more than 2 million tons of copper by 2030.

Rather than guessing at daily copper prices, I prefer the operating play: Quanta Services (PWR), which designs, builds, and maintains the electrical infrastructure connecting new generation to enormous loads like data centers. Its backlog hit $53.4 billion in Q2, including $43.8 billion of electric-infrastructure work. 

The chips sit inside the building; Quanta makes sure the electricity reaches them.

Why I Prefer the AI Infrastructure Suppliers

A $1.7 trillion bill raises an obvious question: who actually pays it? 

Bloomberg’s model shows U.S. hyperscalers swinging from a modest 2025 cash surplus to funding gaps of $130 billion in 2026, $297 billion in 2027, and $140 billion in 2028.

That doesn’t stop the boom. But it does mean operators will lean harder on debt, private credit, infrastructure funds, and joint ventures, and maybe trim buybacks along the way. 

Returns will be uneven, too: Bloomberg models AWS at roughly 24% ROIC in 2026, while newer infrastructure providers start much lower or below zero as they spend ahead of revenue.

This is exactly why I prefer the suppliers. 

The operator has to finance the project, fill the capacity, and eventually earn a return. The companies selling chips, memory, storage, networking, cooling, and electrical gear get paid while the campus is going up.

The pattern running through Bloomberg’s entire model – operators financing while suppliers collect – is the same one at the center of my XPANSE research.

There’s a reason this buildout has Washington’s attention, too. One high-ranking government official has warned that America’s dependence on foreign-made chips could end in what he calls “an economic apocalypse.” 

The race you just read about – trillions of dollars, flowing through every layer of the data center – is also the race to prevent that outcome. And Elon Musk’s next great project sits right in the middle of it.

In my latest briefing, I lay out the three steps I’d take today to get positioned – and give away the name and ticker of my favorite stock for the theme. 

Every gigawatt is getting more expensive. Own the companies sending the invoices.

The post The AI Data Center Bill Keeps Rising. These 7 Stocks Could Collect. appeared first on InvestorPlace.

Before we jump in today, I have big news…

Today marks the inaugural episode of The Investor Place, a brand-new investing podcast hosted by Crystal Navellier, daughter of legendary investor Louis Navellier.

Each episode will bring you fresh market insights, investing ideas, and candid conversations with some of the sharpest minds in the business.

And we’re kicking things off with a big question…

If you had $10,000 to invest right now, where would you put it?

In today’s debut episode, Crystal sits down with three InvestorPlace experts – Louis Navellier, Eric Fry, and Jonathan Rose – to hear their answers.

Click here to watch the debut episode of The Investor Place.

Q3 earnings season begins in earnest today with the big banks reporting, and if you plan to trade it, remember this…

What moves a stock after earnings isn’t necessarily how much money the company made – or lost. It’s how far the results land from what Wall Street expected.

Say Stock A earns $5 a share, but the Street was expecting $9. Despite that healthy profit, the stock will likely get hammered. Meanwhile, Stock B loses $3 a share, but analysts had braced for a $10 loss. Despite the red ink, that stock could very well soar.

The reality is that big moves don’t come from the profit or loss itself; they come from surprises – results far enough from expectations that the market is forced to reprice the stock in a hurry.

So, is there a way to get clues about these surprises before they happen?

There is. And it’s how our trading expert Jonathan Rose, editor of Advanced Notice, approaches every earnings season.

What the pros do differently

Jonathan has spent 28 years in the markets, including time as a market maker – one of the professionals who quote prices on the other side of investors’ trades. That experience shapes how he approaches earnings today.

The average investor plays earnings by picking a stock and guessing which direction it will move after the report. Jonathan and the pros take a different approach. They play what we’ve just highlighted – the difference between reality and expectation.

To do this, they start with two numbers. The first is what we’ll call the “historical move.” Some stocks tend to make big moves after earnings, while others barely budge. Track enough quarters and a pattern emerges for each company.

The second is the “expected move.” Before every report, the options market makes its own prediction about how far a stock will swing in either direction. You can see that prediction in the prices traders are paying for options that expire shortly after the announcement.

Here’s Jonathan on what he does with those two numbers:

If those two numbers line up there’s no edge. The market has done its job.

But when those numbers don’t line up, that’s where opportunity exists. And I don’t need to guess direction to take advantage of it.

I’m not relying on being perfectly right. I’m putting myself in a position where if the move is bigger than expected, I get paid.

Jonathan and his subscribers use this approach every earnings season. They don’t try to predict – they position.

The good news is that Jonathan just flagged a handful of these opportunities.

Here’s Jonathan, talking about yesterday’s free episode of Masters in Trading LIVE:

Right now, I’ve got 34 names on the board. The data picked just six to buy — and three we shouldn’t touch with a 10-foot pole.

[In yesterday’s episode], I break down the six key names flashing buy signals right now and the process that we us every earnings season to collect market-beating gains.

If you want to trade surprises this earnings season, this episode is the place to start.

A second way that the market signals a trading opportunity

The gap between historical and expected moves is one way Jonathan looks for an edge. But the tool at the center of his trading is his scanner for unusual options activity.

Jonathan built it to detect unusually large options trades, which are often the footprints of institutional players placing high-conviction bets. Time and again, these trades have foreshadowed major price moves before they hit the mainstream radar. For traders who spot them and position themselves accordingly, the result can be fast, triple-digit returns that the average investor misses.

Back to Jonathan:

Most traders wait for CNBC to tell them a stock is rallying. By then, the move is already over.

But when you learn to read the options flow? When you understand what the expected move is signaling? You’re trading with the same information institutions are using.

Jonathan will cover his entire system tomorrow night at 8 p.m. Eastern during his free $10K to $100K Challenge. Here is what to expect:

At this special event, I’m walking you through everything my playbook has to offer — from the principles behind our trades to the charts, tools and process I use to look for an edge in the market.

This is the same playbook that’s netted readers AI winners like BFLY and DOX, where unusual options activity helped us collect gains of 219% and 534% — and even returns as high as 779% and 1,076% on OXY and BMY, respectively.

To be clear, you don’t need a huge trading account to get started. Every trade Jonathan recommends has a defined maximum loss, and readers can enter each position for less than $500. How much you put at risk is always your decision.

Just click here to reserve your seat for the free event, and we’ll see you tomorrow night.

The $20 billion question hanging over AI

Last Thursday, a single news report knocked the wind out of AI stocks.

The Financial Times reported that OpenAI told investors its annualized revenue was approaching $50 billion at the end of September. The problem was that, just a couple of weeks earlier, widely circulated reports had put that figure at $68 billion to $70 billion.

That’s a $20 billion gap for the company sitting at the center of the AI boom, with massive implications for the broader AI trade. For example, according to an analysis by venture capitalist Tomasz Tunguz, OpenAI has committed to roughly $1.15 trillion in computing infrastructure through 2035.

Chipmakers, cloud providers, and data center builders have built revenue forecasts – which flow through to stock prices – on the assumption that OpenAI’s sales will grow fast enough to pay its bills. If those sales are meaningfully smaller than the market believed, the commitments stacked on top of them start to look shakier – which means today’s stock prices are shakier.

And this is what happened last Thursday…

In the wake of that report, Wall Street panicked and immediately sold. The Nasdaq suffered its worst day since mid-August, with the heaviest damage among companies most tied to OpenAI’s spending, such as Nvidia (NVDA), Oracle (ORCL), and CoreWeave (CRWV).

So, was last Thursday’s selloff justified?

Our technology expert Luke Lango, editor of Innovation Investor, doesn’t think so. Here he is from last week’s Daily Notes:

We think that report is a nothing burger.

The discrepancy comes down to the difference between gross and net accounting – nothing more.

It says nothing about overall AI demand, which by every measure, including those same revenue numbers, is robust and accelerating.

To see what Luke means, it helps to know how AI companies count their sales.

Many businesses buy access to OpenAI’s and Anthropic’s models through cloud platforms such as Microsoft’s (MSFT) Azure or Amazon (AMZN) Web Services, and the cloud provider takes a cut of each sale. Anthropic counts the full value of those sales as revenue, then books the partner’s share as an expense. OpenAI counts only the portion it keeps.

Neither approach is wrong, but they produce very different numbers. The roughly $70 billion figure that circulated in September was a recalculation of OpenAI’s sales using Anthropic’s method, so investors could compare the two companies side by side.

The $50 billion figure is OpenAI’s own “net” count. Put the bigger number next to the smaller one, and you get a $20 billion “shortfall” in sales that was never lost.

Once you compare apples to apples, the picture changes completely. Back to Luke:

On a consistent net basis, OpenAI’s run rate increased from about $30 billion in July to $50 billion in September. On a gross basis, it increased from about $40 billion to $70 billion.

Both comparisons show growth of roughly 70% over that period.

That lines up with what OpenAI reportedly told its own investors: total run-rate growth of 77% during the third quarter, and 107% growth in its enterprise business.

Better still, the growth is speeding up…

By Luke’s estimates, OpenAI’s run rate barely moved from March through June. Then it broke sharply higher, with net growth climbing from about 20% in July to 27% in August and 32% in September.

Year over year, he estimates OpenAI’s growth accelerated from about 131% in June to 229% in September.

Here’s Luke’s bottom line:

The takeaway: The market appears to have mistaken an accounting distinction for a demand slowdown, even as OpenAI’s underlying growth was accelerating.

Just a reminder – it’s wise to avoid a knee-jerk reaction to every bearish headline. Sometimes, the media is more interested in clicks than accuracy.

Finally, a different way to play oil

As the Middle East conflict drags on, we’ve brought you plenty of ideas for playing oil here in the Digest. Today, let’s look at a corner of the energy trade that’s been on fire: the ships that carry the oil.

The numbers are startling. At the start of the year, a supertanker carrying about 2 million barrels of crude from the Middle East to Asia earned roughly $30,000 a day, according to shipbroker Poten & Partners. That rate recently hit $1.3 million a day. Meanwhile, nine of the 13 U.S.-listed tanker stocks have more than doubled this year.

Can the run continue?

Legendary investor Louis Navellier, editor of Accelerated Profits, thinks so.

In last week’s issue, when a subscriber asked him to name his top tanker pick, Louis had trouble choosing:

Asking me to pick my favorite tanker company in the current environment is like asking me to pick my favorite child!

What we need to remember is that most crude oil tanker companies will continue to thrive in the coming months for one specific reason: Crude oil prices are not going to moderate significantly.

Normally, energy prices soften in the fall as seasonal demand slows. But Louis points out that global crude oil and natural gas inventories have been depleted, and countries around the world need to refill their stockpiles.

Here he is with the takeaway:

So, crude oil prices aren’t likely to fall below $90 per barrel.

With energy prices to remain elevated for the foreseeable future and no end in sight to the geopolitical tensions overseas, shipping rates are expected to remain high.

So, tanker companies are expected to continue to make money hand over fist, as they transport crude oil around the world.

Louis has recently added several tanker companies to the Accelerated Profits Buy List. One of his favorites is Okeanis Eco Tankers Corp. (ECO), a Greece-based owner of modern supertankers. Since Louis recommended it on June 22, ECO is up 91%.

For the rest of Louis’ tanker picks, click here to learn more about joining him in Accelerated Profits.

We’ll keep you updated on all these stories here in the Digest.

Have a good evening,

Jeff Remsburg

(Disclosure: I own AMZN, MSFT)

The post The $20 Billion AI Scare That Wasn’t appeared first on InvestorPlace.

Today, I’m explaining how I find opportunities exactly like that in one segment of the market that’s slightly off the beaten path – closed-end funds. I’ll explain the massive discounts they provide – and I’ll even share two examples that show why the biggest discount isn’t necessarily the best bargain.

This isn’t the only opportunity I’m putting on your radar today.

Tomorrow night at 8 p.m. Eastern, I’m going live to explain my broader trading strategy during my free $10K to $100K Challenge.

Reserve your spot here.

There, I’ll show you everything my approach has to offer — from the principles behind our trades to the charts, tools and process I use to look for an edge in the market.

And here’s the best part: You don’t need $10,000 to get started. I’ll show you how to apply the same approach to smaller trades, including opportunities where you can keep the amount at risk below $500.

I hope to see you there. Again, here’s that sign-up link.

Back in early 2015, investors wanted a piece of Cuba.

Washington was restoring relations with the island. And so, retail investors started dreaming about American tourists, new business, and opportunities that had been off-limits for decades.

So they took to their laptops and went looking for something to buy.

And there it was, right on their screens: CUBA. A ticker practically handing them the trade they were looking for.

Except there was a problem.

The fund’s actual name was the Herzfeld Caribbean Basin Fund. And when I looked under the hood, it didn’t own Cuban stocks. It owned businesses operating around the Caribbean, including airlines and cruise companies, but there was no Cuba in the CUBA fund.

Zero.

Nevertheless, excitement about the island nation had pushed the fund’s share price well above the value of what it owned.

People were paying extra for the story.

I took a short position against that inflated price, and it became one of the biggest trades I’ve personally had.

Now, I’m not asking you to make that trade… or to short anything. I’m telling you this story because the same disconnect can work in the other direction.

Sometimes investors pay too much for a basket of stocks. Other times, Wall Street sells you that basket for less than the value of the stocks inside.

That’s where you want to shop.

Today, I’ll show you how buying stocks at a discount works, walk through two examples, and explain the comparison I make before I call anything a bargain — because a discount by itself doesn’t mean a thing.

To get these stocks at a discount, you don’t have to wait for the whole market to go on sale.

Buying a Dollar’s Worth of Stocks for Less Than a Dollar

Think about a basket of stocks worth $100.

You add up the holdings, subtract what the fund owes, and that’s what you have: $100 in net assets.

But investors are buying and selling shares of the fund itself. And sometimes the price they’re willing to pay represents only $85 of that $100.

That’s a 15% discount, and you’re buying your share of the basket for less than its underlying value.

The vehicle that makes this possible is called a closed-end fund. Don’t let the name intimidate you.

I actually used to teach this exact strategy under the name “closed-end fund arbitrage”… and nobody joined. Called it “hedge fund secrets” the next month, same exact content, and a crowd of folks signed up.

Moving on.

A closed-end fund’s shares trade on an exchange, just like a stock. But the share price can move away from the value of its holdings, creating a discount – or a premium.

Don’t get me wrong. This doesn’t get you a special price on individual shares of Microsoft Corp. (MSFT) or Nvidia Corp. (NVDA). Instead, you’re buying shares of a fund that owns those stocks.

And that gives us another price relationship to study.

And here’s the rule I never break: A discount by itself doesn’t tell you whether something is cheap. Nothing is ever cheap or expensive on its own.

It drives me crazy when people say a stock is “oversold” without telling me relative to what. It’s like that scene in Major League where the fan yells, “That can’t be a home run, it’s too high!” You can’t be too high. It’s a home run.

Suppose a fund is selling at a 20% discount. Sounds great, right? But what if it usually trades at a 20% discount? Then you haven’t necessarily found anything unusual. That could be a big old nothingburger.

If it normally trades at a 3% discount and now it’s sitting at 15%, now we’ve got something. Now I want to know what changed.

Did something happen to the holdings? Are the fees too high? Or have investors pushed the fund’s price down more than the underlying portfolio?

We compare the fund to itself. Then we do the research.

Two Places to Look for Discounted Stocks

One of my favorite examples right now is Eaton Vance Enhanced Equity Income Fund II (EOS).

Look inside and you’ll recognize the names immediately: Alphabet Inc. (GOOG), Amazon.com Inc. (AMZN), Apple Inc. (AAPL), Broadcom Inc. (AVGO), Microsoft, and Nvidia.

As of October 6, EOS closed at $21.56 while its net assets were worth $24.87 per share. That’s a 13.31% discount. Its one-year average discount is around 8%. That gap is what gets my attention.

Now, EOS uses an income strategy that can limit some upside versus owning the stocks outright. You’re buying the fund’s approach along with its holdings. Understand what you own.

But right now? I haven’t seen a discount this wide on EOS in quite some time. This is one of the better closed-end fund setups I’ve seen in a while.

But let’s use some round numbers to explain the discount opportunity.

Imagine a basket worth $100. You buy your share for $87.

Now suppose the basket stays worth $100, but the discount narrows. Investors become willing to pay $92 for it. Your investment has gained about 5.7%, even though the underlying basket hasn’t increased in value.

That’s a hypothetical example, before fees and distributions. It isn’t a prediction.

It shows you why I watch the relationship between those two prices. The stocks don’t have to do all the work.

The second example I walked through recently on Masters in Trading LIVE was ASA Gold and Precious Metals Ltd. (ASA). This fund invests primarily in companies involved in precious metals mining. So you’re looking at a very different basket from EOS.

During the broadcast, the screen showed ASA at roughly a 20% discount, versus an average around 13%. Again, that comparison gives us a reason to investigate.

If you want exposure to precious metals stocks, this could be a better entry than paying full value for the basket. But you still have to like what’s inside.

A discount doesn’t make mining stocks safe. And buying technology stocks through EOS doesn’t remove their market risk.

These are candidates to research, not automatic “Buys.” Check the latest prices and holdings before making a decision.

Find the Discount, and Then Find the Reason

This is also a good time of year to build a watchlist.

Late-year tax-loss selling can put additional pressure on some funds as investors sell losing positions. That can create wider discounts worth investigating.

I’m not buying every fund that falls. But I am looking for a few opportunities where the price relationship has become unusually attractive.

On my show, I pulled up a free screening tool and worked through these comparisons with viewers. You can check the current discount, compare it with the fund’s history, and look at what it owns.

Then ask the questions that matter:

Why is it discounted? What would make the discount narrow? How much am I comfortable risking? What would tell me the trade isn’t working?

Because the discount can widen. The holdings can fall. And there’s no guarantee you’ll ever be able to sell at the full value of the underlying assets.

That’s why we need a plan.

The Cuba trade worked for me because I looked past the ticker and compared the price with what I was actually buying.

Looking for discounted stocks requires that same habit.

Let’s Take the Next Step Together

That’s the kind of thinking I want to teach you: how to get beyond an interesting headline and work through an actual trading opportunity.

On Wednesday, October 14, at 8 p.m. Eastern, I’m holding my free $10K to $100K Challenge. (Click here to reserve your free spot.)

Buying discounted baskets is one approach I’ve taught. During the Challenge, I’ll go deeper into the strategy behind my Advanced Notice trades, including how I look for signs of large investors positioning before the broader public catches on, and how I turn those signals into specific trades.

You’ll also learn why, despite the event’s name, you don’t need $10,000 to begin using the strategy. I’ll show you how a trade can be structured with less than $500 at risk.

Back in the Cuba frenzy, investors found an exciting name and paid extra to own it.

I want you to develop a different instinct. Look inside. Compare the prices. Understand the risk.

And when you find stocks you want to own, ask one more question: Is there a way to buy this basket at a discount?

Remember, the creative trader wins.

Jonathan Rose

Founder, Masters in Trading

The post How to Buy a Dollar’s Worth of Stocks for Less Than a Dollar appeared first on InvestorPlace.

Well, my friend and colleague Jonathan Rose knows a thing or two about finding opportunities like these.

Jonathan has spent nearly three decades in the markets, including time as a professional market maker. He knows how Wall Street works, and he has a knack for spotting opportunities that most investors overlook.

That’s why I’m excited to share his insights with you today. Below, Jonathan reveals two funds trading at a discount – and explains how to tell whether you’re getting a real bargain.

But I also want to make sure you know about a special opportunity to learn directly from Jonathan.

Tomorrow, Wednesday, October 14, at 8 p.m. Eastern, Jonathan is hosting his free $10K to $100K Challenge.

He’s going to share the strategy he believes could help investors turn $10,000 into $100,000 or more over the next year.

Now, I’ve been in this business a long time, and I can tell you that finding someone with Jonathan’s experience and understanding of the markets is no small thing. I wouldn’t be sharing this opportunity with you if I didn’t think he had something valuable to teach you.

And with the event happening tomorrow, I don’t want you to miss your chance to hear what he has to say.

Click here to save your free seat for tomorrow’s $10K to $100K Challenge.

Now, I’ll turn things over to Jonathan.

****************************

Hey, guys.

Back in early 2015, investors wanted a piece of Cuba.

Washington was restoring relations with the island. And so, retail investors started dreaming about American tourists, new business, and opportunities that had been off-limits for decades.

So they took to their laptops and went looking for something to buy.

And there it was, right on their screens: CUBA. A ticker practically handing them the trade they were looking for.

Except there was a problem.

The fund’s actual name was the Herzfeld Caribbean Basin Fund. And when I looked under the hood, it didn’t own Cuban stocks. It owned businesses operating around the Caribbean, including airlines and cruise companies, but there was no Cuba in the CUBA fund.

Zero.

Nevertheless, excitement about the island nation had pushed the fund’s share price well above the value of what it owned.

People were paying extra for the story.

I took a short position against that inflated price, and it became one of the biggest trades I’ve personally had.

Now, I’m not asking you to make that trade… or to short anything. I’m telling you this story because the same disconnect can work in the other direction.

Sometimes investors pay too much for a basket of stocks. Other times, Wall Street sells you that basket for less than the value of the stocks inside.

That’s where you want to shop.

Today, I’ll show you how buying stocks at a discount works, walk through two examples, and explain the comparison I make before I call anything a bargain — because a discount by itself doesn’t mean a thing.

To get these stocks at a discount, you don’t have to wait for the whole market to go on sale.

Buying a Dollar’s Worth of Stocks for Less Than a Dollar

Think about a basket of stocks worth $100.

You add up the holdings, subtract what the fund owes, and that’s what you have: $100 in net assets.

But investors are buying and selling shares of the fund itself. And sometimes the price they’re willing to pay represents only $85 of that $100.

That’s a 15% discount, and you’re buying your share of the basket for less than its underlying value.

The vehicle that makes this possible is called a closed-end fund. Don’t let the name intimidate you.

I actually used to teach this exact strategy under the name “closed-end fund arbitrage”… and nobody joined. Called it “hedge fund secrets” the next month, same exact content, and a crowd of folks signed up.

Moving on.

A closed-end fund’s shares trade on an exchange, just like a stock. But the share price can move away from the value of its holdings, creating a discount – or a premium.

Don’t get me wrong. This doesn’t get you a special price on individual shares of Microsoft Corp. (MSFT) or Nvidia Corp. (NVDA). Instead, you’re buying shares of a fund that owns those stocks.

And that gives us another price relationship to study.

And here’s the rule I never break: A discount by itself doesn’t tell you whether something is cheap. Nothing is ever cheap or expensive on its own.

It drives me crazy when people say a stock is “oversold” without telling me relative to what. It’s like that scene in Major League where the fan yells, “That can’t be a home run, it’s too high!” You can’t be too high. It’s a home run.

Suppose a fund is selling at a 20% discount. Sounds great, right? But what if it usually trades at a 20% discount? Then you haven’t necessarily found anything unusual. That could be a big old nothingburger.

If it normally trades at a 3% discount and now it’s sitting at 15%, now we’ve got something. Now I want to know what changed.

Did something happen to the holdings? Are the fees too high? Or have investors pushed the fund’s price down more than the underlying portfolio?

We compare the fund to itself. Then we do the research.

Two Places to Look for Discounted Stocks

One of my favorite examples right now is Eaton Vance Enhanced Equity Income Fund II (EOS).

Look inside and you’ll recognize the names immediately: Alphabet Inc. (GOOG), Amazon.com Inc. (AMZN), Apple Inc. (AAPL), Broadcom Inc. (AVGO), Microsoft, and Nvidia.

As of October 6, EOS closed at $21.56 while its net assets were worth $24.87 per share. That’s a 13.31% discount. Its one-year average discount is around 8%. That gap is what gets my attention.

Now, EOS uses an income strategy that can limit some upside versus owning the stocks outright. You’re buying the fund’s approach along with its holdings. Understand what you own.

But right now? I haven’t seen a discount this wide on EOS in quite some time. This is one of the better closed-end fund setups I’ve seen in a while.

But let’s use some round numbers to explain the discount opportunity.

Imagine a basket worth $100. You buy your share for $87.

Now suppose the basket stays worth $100, but the discount narrows. Investors become willing to pay $92 for it. Your investment has gained about 5.7%, even though the underlying basket hasn’t increased in value.

That’s a hypothetical example, before fees and distributions. It isn’t a prediction.

It shows you why I watch the relationship between those two prices. The stocks don’t have to do all the work.

The second example I walked through recently on Masters in Trading LIVE was ASA Gold and Precious Metals Ltd. (ASA). This fund invests primarily in companies involved in precious metals mining. So you’re looking at a very different basket from EOS.

During the broadcast, the screen showed ASA at roughly a 20% discount, versus an average around 13%. Again, that comparison gives us a reason to investigate.

If you want exposure to precious metals stocks, this could be a better entry than paying full value for the basket. But you still have to like what’s inside.

A discount doesn’t make mining stocks safe. And buying technology stocks through EOS doesn’t remove their market risk.

These are candidates to research, not automatic “Buys.” Check the latest prices and holdings before making a decision.

Find the Discount, and Then Find the Reason

This is also a good time of year to build a watchlist.

Late-year tax-loss selling can put additional pressure on some funds as investors sell losing positions. That can create wider discounts worth investigating.

I’m not buying every fund that falls. But I am looking for a few opportunities where the price relationship has become unusually attractive.

On my show, I pulled up a free screening tool and worked through these comparisons with viewers. You can check the current discount, compare it with the fund’s history, and look at what it owns.

Then ask the questions that matter:

Why is it discounted? What would make the discount narrow? How much am I comfortable risking? What would tell me the trade isn’t working?

Because the discount can widen. The holdings can fall. And there’s no guarantee you’ll ever be able to sell at the full value of the underlying assets.

That’s why we need a plan.

The Cuba trade worked for me because I looked past the ticker and compared the price with what I was actually buying.

Looking for discounted stocks requires that same habit.

Let’s Take the Next Step Together

That’s the kind of thinking I want to teach you: how to get beyond an interesting headline and work through an actual trading opportunity.

Tomorrow, October 14, at 8 p.m. Eastern, I’m holding my free $10K to $100K Challenge. (Click here to reserve your free spot.)

Buying discounted baskets is one approach I’ve taught. During the Challenge, I’ll go deeper into the strategy behind my Advanced Notice trades, including how I look for signs of large investors positioning before the broader public catches on, and how I turn those signals into specific trades.

You’ll also learn why, despite the event’s name, you don’t need $10,000 to begin using the strategy. I’ll show you how a trade can be structured with less than $500 at risk.

Back in the Cuba frenzy, investors found an exciting name and paid extra to own it.

I want you to develop a different instinct. Look inside. Compare the prices. Understand the risk.

And when you find stocks you want to own, ask one more question: Is there a way to buy this basket at a discount?

Remember, the creative trader wins.

Jonathan Rose

Founder, Masters in Trading

P.S. Jonathan’s Cuba story makes a useful point: An exciting investment story and an attractive purchase price are two different things. I encourage you to keep learning from him at his free $10K to $100K Challenge tomorrow, October 14 at 8 p.m. Eastern. He’ll explain the signals behind his best trades and how he evaluates the opportunity and risk, giving you a closer look at the process behind his ideas. Save your spot here.

The post How to Buy Stocks for Less Than They’re Worth appeared first on InvestorPlace.

It is a watch.

Not gold. Not flush with jewels. Just a simple watch, ticking away in a box belowdecks.

It doesn’t make the ship any faster. It doesn’t calm the violent Atlantic waves. But it may answer the question that has haunted seafarers since the first hull left sight of shore…

Where, exactly, are we?

For generations, that question had no reliable answer. Latitude, sailors could find by the stars. Longitude — a measure of position running east to west — could only be calculated if sailors carried an accurate record of time from their home port across an ocean whose rolling and humidity constantly threatened to throw every timekeeping mechanism off course. 

Enter John Harrison. 

Harrison was not a scientist by training, but a carpenter, self-taught in the language of gears and escapements. He had spent most of his adult life chasing a single obsession: a watch that could survive the sea.

His fourth attempt, H4, was the watch aboard that ship. His son William held it in trust, checking it daily, trusting it over the instincts of men who had sailed these waters for decades.

And when H4 predicted the crew would spot Madeira before the sailors believed it possible… It was right.

The island appeared exactly when the little watch said it would.

A small machine, no larger than a dinner plate, had just quietly solved one of the most expensive, most deadly problems in the history of navigation.

There’s a lesson buried in that story: an enterprise of staggering scale can hinge on a component few think to look for.

I’d argue the same principle is quietly reshaping the AI economy today.

Everyone is watching the chips, or the data centers, or the spending commitments stacking into the hundreds of billions.

Almost no one is watching the clock.

Yet precision timing has become one of the unglamorous necessities of the AI buildout. It’s the synchronization that lets massive, expensive systems operate as one coherent machine instead of a thousand disconnected parts. In the latest episode of Being Exponential with Luke Lango, we examine a company doing exactly that.

It’s a timely opportunity, if you’ll forgive the pun, because the broader market right now feels like two different economies wearing the same face.

Borrowing costs still bite. Consumers are stretched thin. Half the stock market looks nothing like the half that keeps making headlines.

So which is it? Should investors wait for conditions to improve, or are they hunting for growth in all the wrong corners?

My take: the AI earnings engine is accelerating even as the rest of the economy strains under its own weight. Understanding that divergence is how you find proven winners.

So let’s follow the thread from the market’s current tug-of-war, to an overlooked component supplier keeping time for billion-dollar machines, to a financing headline that looks alarming right up until you check the math.

Earnings Are Pulling Harder

The market framework I keep coming back to is simple: higher interest rates versus higher earnings.

Higher rates make borrowing more expensive and reduce what investors are willing to pay today for profits expected years from now. That creates a headwind for growth stocks.

Rising earnings pull the other way.

In the episode, we discuss encouraging signs from across AI infrastructure: Marvell’s stronger outlook, AMD CEO Lisa Su’s comments about demand and supply constraints, and similar demand commentary from Nokia.

Those signals matter because they help connect enthusiasm about AI with the businesses supplying it.

A bigger addressable market alone doesn’t pay the bills. Orders, shipments and profitable revenue do. The more spending converts into those results, the stronger the earnings side becomes.

That’s why stocks can advance before the interest-rate problem disappears.

Suppose a company earns $5 a share and trades at 30 times earnings. That’s a $150 stock. If earnings rise to $7 while its valuation falls to 25 times earnings, the stock reaches $175.

Investors paid a lower multiple. The share price still rose.

That’s an illustration, not a price target. But it explains why waiting for an all-clear on rates can mean missing an earnings-driven advance.

Follow the Spending Beyond the Obvious Names

This also explains why a rising index can coexist with a lot of struggling stocks.

A consumer business depends on households having the money and confidence to spend. An AI infrastructure supplier may depend on technology companies expanding computing capacity.

Those are different customers with different budgets.

That’s the AI Bifurcation we keep discussing. You can have weakness in one part of the economy and powerful investment growth in another.

For investors, the useful question becomes: Where does the AI spending actually go?

Some goes to computing providers such as Nebius (NBIS). Some goes to networking and semiconductor suppliers. Some goes toward the electricity required to run everything, which is why we also discuss Constellation Energy in the episode.

These businesses offer different forms of exposure, with different financing needs, competitive pressures and valuations. Being farther from the computing layer doesn’t automatically make a stock safer.

But it does expand the opportunity set.

You don’t have to predict which chatbot wins every customer to investigate the businesses supplying infrastructure that many competing platforms need.

The Tiny Clocks Behind the Giant Machines

Which brings us back to Harrison’s watch, and to SiTime (SITM).

SiTime makes precision timing products. Think of them as part of the heartbeat of electronic systems.

Inside an AI data center, processors, networking equipment and communications links must coordinate activity. Timing errors can create delays and waste expensive computing capacity.

The financial logic is straightforward: If a component helps costly equipment do more useful work, its importance can far exceed its size.

Traditional timing devices often rely on quartz. SiTime builds products using silicon MEMS — microelectromechanical systems — with advantages in demanding conditions, including temperature changes and vibration.

In May, the company introduced a timing product specifically designed to improve synchronization and GPU utilization in AI data centers. That is a concrete example of timing technology being developed around AI’s operating demands.

I see two potential growth drivers here.

First, the infrastructure buildout creates more systems that need timing components.

Second, increasingly demanding systems can create opportunities to upgrade those components.

That combination is why I’m enthusiastic about SiTime. More infrastructure can expand demand, while better performance requirements can create room for more advanced products.

It doesn’t make the stock a buy at any price. The investment case still depends on execution, adoption and valuation.

But it illustrates exactly the kind of overlooked business I want investors to understand.

Track the Customer, Not Just the Construction

Of course, infrastructure enthusiasm needs an economic foundation.

That’s why we follow revenue growth at OpenAI and Anthropic so closely. Their ability to turn AI usage into paying business is an important signal about the demand supporting this buildout.

One measure discussed in the episode is annualized revenue run rate, or ARR.

Think of it as a snapshot of the current revenue pace extended over a year. It is not necessarily the amount already earned over the previous 12 months, guaranteed future revenue or profit. Definitions also deserve scrutiny.

The useful signal is the trajectory: Is paid demand continuing to expand fast enough to support the investment happening around it?

For diversified companies, that demand can be harder to isolate. Cloud growth can provide clues, but cloud revenue includes more than AI.

No single number settles the debate. I want to see customer monetization, supplier revenue and infrastructure commitments reinforcing one another.

A Scary Headline Still Needs a Denominator

The episode also tackles a subscriber’s concern about SoftBank borrowing against its Arm (ARM) shares.

Borrowing against a volatile asset creates risk. But the loan amount alone doesn’t tell you how much.

Using the figures discussed in the episode — 769 million pledged shares, an assumed $300 share price and a $25 billion loan — the collateral would be worth approximately $230.7 billion.

That puts the loan at about 10.8% of collateral value.

Under those assumptions, Arm would have to fall roughly 57% for the ratio to reach 25%, assuming the debt and pledged share count stayed unchanged.

That 25% figure is an illustration, not a verified margin-call trigger. Actual lending terms matter, and a low starting ratio doesn’t eliminate refinancing or forced-selling risk.

Still, the exercise helps separate a frightening headline from the financing question underneath it.

Before deciding how worried to be, do the math.

What I’m Watching Next

I’m constructive on the outlook for November and December because I think earnings can keep strengthening while some of the pressure from rates eases.

That is a forecast. The timing of geopolitical relief and changes in borrowing costs remains uncertain.

What would challenge my view? Slower AI monetization, weaker supplier outlooks or meaningful cuts to infrastructure spending. Those would matter more than a reassuring headline about the calendar.

For now, I’m focused on businesses turning AI demand into revenue — and solving problems that become more important as the buildout grows.

In the full episode of Being Exponential, Brooke and I work through the market outlook, the SiTime thesis and the Arm financing question in more detail.

Watch the full conversation to see how those pieces fit together, and leave us a question for a future episode.

Harrison’s watch helped sailors locate their ships. For investors, the exercise is locating the indispensable parts of this enormous buildout.

Some of them are very small indeed.

P.S. My colleague Jonathan Rose has an ambitious goal: Show folks how they could turn $10,000 into $100,000 using his trading strategy. On Wednesday, October 14, at 8 p.m. Eastern, he’ll explain his approach during the free $10K to $100K Challenge. Jonathan brings decades of professional trading experience — and a knack for making the lessons understandable. Sign up here to see how he finds opportunities, plans his trades, and decides what he’s willing to risk.

The post The AI Boom Has a Clock Problem (And It’s Your Biggest Opportunity) appeared first on InvestorPlace.