Behind the greatest investment wealth creation in modern history are … computers. How a data-analytics market approach dominates
Jim Simons was suicidal.
In 1979, a young staffer found the hedge fund manager lying on his couch, still reeling from a bad bet on bond-futures contracts.
The mistimed call had lost nearly a million dollars of client money, which was substantial given the tiny size of Simons’ investment shop at the time.
“Sometimes I look at this and feel I’m just some guy who doesn’t really know what he’s doing,” lamented Simons.
Little did he know, he would go on to become the most successful money maker in the history of modern finance.
***The unprecedented success of Jim Simons
Investors like Warren Buffett and George Soros get the headlines, but when it comes to long-term returns, Jim Simons is the big dog.
Starting in 1988, through 2018, his flagship Medallion fund posted average annual returns of 66%. That equates to trading gains of more than $100 billion.
No other hedge fund manager even begins to approach those numbers. See for yourself below (and realize that you’re seeing after-fee returns to investors). Also, notice how Simons’ returns almost doubled those of Buffett.
So, what was Simons’ background that was the bedrock of this success?
Did he have a Masters in Business? Countless finance classes in which he learned high-brow investment analysis methods? Years of studying macro factors to predict changes to the broader economy?
No.
Simons was simply a mathematician who decided to try his hand at trading currencies. And yet somehow, this was his result over three decades of volatile markets …
***What was the market strategy behind Simons’ success?
From The Wall Street Journal:
For a while, Mr. Simons traded like most everyone else, relying on intuition and old-fashioned research. But the ups and downs left him sick to his stomach.
After realizing his approach wasn’t working for him, he turned toward something else …
Math.
Simons built a high-tech trading system guided by preset algorithms — basically, step-by-step computer instructions. It was a program designed to digest vast quantities of market data and identify attractive trades based on Simons’ parameters.
The goal was simple — find an edge through quantitative methods, remove human emotion and instinct from the investment selection process, then rinse and repeat.
Simons told a friend, “I don’t want to have to worry about the market every minute. I want models that will make money while I sleep. A pure system without humans interfering.”
***The importance of using numbers in your stock selection process
Using numbers as the basis of a stock selection process would improve the performance of most investors purely by helping them get out of their own way. That’s because, as it did with Simons, it would remove emotion from the process.
The research company, Dalbar, has documented the underperformance of the average investor (largely due to emotions). In a long-term study that tracked investors from 1986 to 2015, Dalbar found that the average investor’s returns were just 3.66% per year, compared to the S&P 500’s annual return of 10.35%.
But there’s another reason why investors stand to benefit from a numbers-approach to the stock market even beyond sidestepping their own emotions …
Most stocks are terrible investments, and a quant approach could help avoid them.
About a decade ago, the team at Longboard studied the total lifetime returns for individual U.S. stocks from 1983 through 2006.
In short, the study found that the worst performing 6,000 stocks — which represented 75% of the stock-universe in the study — collectively had a total return of … 0%.
The best performing 2,000 stocks — the remaining 25% — accounted for all of the gains.
Source: Longboard
Here’s Longboard on the takeaway:
The conclusion is that if an investor was somehow unlucky enough to miss the 25% most profitable stocks and instead invested in the other 75% his/her total gain from 1983 to 2006 would have been 0%. In other words, a minority of stocks are responsible for the majority of the market’s gains.
But this isn’t the end of it. If we dive into this study on a more granular level, it’s even more sobering.
The above statistic, that 75% of the stocks had a collective return of 0%, masks a darker truth. While it would be unfortunate to sink your money into a stock that generated nothing, you might be fooled into thinking that you’d at least walk away with your original investment capital. Not so fast …
The Longboard study found that 18.5% of stocks lost at least 75% of their value.
In other words, nearly one in five stocks didn’t just return nothing, they were double-digit losers that destroyed investment capital.
Here’s the breakdown:
Source: Longboard
Other studies have found similar results.
Research from Hendrik Bessembinder, which looked at equities from 1926 to 2015, concluded that about 60% of stocks were so bad that their performance was worse than one-month U.S. Treasury notes.
From Bessembinder:
It is historically the norm in the U.S. and around the world that a few top-performing companies have great influence over how the market does overall. It’s the norm and I expect it to be the case in the future.
While it may be “the norm,” it points toward a sobering takeaway for investors …
It’s not easy to find big winners — because very few big winners actually exist.
And if you don’t find a big winner, getting a 0% return isn’t the worst potential outcome. Instead, significant loss of your hard-earned money is a very real threat — and it happens with greater frequency than many investors realize.
Facing odds like this, using numbers to help identify the most superior stocks takes on even more importance.
***Here at InvestorPlace, our own Louis Navellier has been using a numbers-based approach to the markets for decades
From Louis:
I’m a numbers guy. Always have been. Since I was a kid, I’ve loved math and I knew that math was the right way to understand the world.
Said another way, I depend on evidence for my decisions.
As to the results of Louis’ numbers-based approach, here’s a screenshot of just a few of his winners, including the time-period in which those gains occurred.
***Louis isn’t the only numbers-based analyst at InvestorPlace today
Regular Digest readers will recognize the name “Stefanie Kammerman.” She’s the analyst behind the “Dark Pool” strategy which we’ve profiled in many Digest issues now.
Like Louis, Stefanie doesn’t invest according to hunches or gut-feel. Instead, she simply uses computers to follow the Dark Pool money-trail by monitoring “prints” — in other words, a record of a market transaction. These prints alert her to various trades.
Once she’s in a trade, she follows certain exit-timing rules to guide her profit-taking and risk-mitigation. Again, the name of the game is “remove emotions.”
So, how has Stefanie’s numbers-based approach been performing?
Recently, she recommended a bullish trade on Verizon based on the prints she was seeing.
Last Friday, Verizon made a big move as her system had suggested. Given the move, she recommended closing half of her bullish trade for a 100% return on capital. However, she noted that given the timing of when someone actually closed their trade, the return could have been as high as 247%.
Yesterday, Stefanie suggested closing another one-quarter position of the bullish trade, this time for a return on capital of 200%.
The final quarter-position remains open for now.
By the way, if you’re interested in subscribing to Stefanie’s Dark Pool Trader newsletter, it’s going to be available mid-month. More details to come.
***Would a numbers-based approach help you in our current market environment?
Today, investors face endless uncertainties.
The shape and length of our economic recovery … the potential for a COVID-19 resurgence … the timing of a COVID-19 vaccine … escalating tension with China … stark socioeconomic polarization in our nation fueling the potential for more social unrest …
Three questions:
What’s your “hunch” as to how all of this will impact your portfolio?
Do you have any anxiety that your hunch could be wrong?
Might it bring you greater peace to adopt an investment approach that doesn’t require your hunch to be right?
It’s worked for Jim Simons, Louis Navellier, and Stefanie Kammerman. Perhaps it’s time to see how it might work for you.
Have a good evening,
Jeff Remsburg
