These days, the concept of automation is so pervasive we almost take it for granted. We don’t bat an eyelash as we scan our groceries through self-checkout, program our DVRs to record what we want, set our thermostats to adjust automatically at various times of the day, and more. So, when Tesla Motors (TSLA) announces a self-driving car, we think, “Didn’t Google do that already?”
Now, there’s a new crop of robots embedding themselves into our daily goings-on — except this time, they’re handling our finances. Robo-advisors, or automated investment services, have taken the Street by storm, and tensions are beginning to rise between the machines and the 300,000 human financial advisors now wondering if their jobs are at risk.
Two tech startups, Betterment and SigFig, have already begun to implement robo-advisors as their main platforms, using algorithms to manage their customers’ investment portfolios based on age, income and risk tolerance.
Most robo-managed accounts on the market today boil down to simple allocations from a very limited shelf of pre-built portfolios. It’s really nothing that you couldn’t do on your own. That’s okay though, because the goal is very different from real hands-on investing, which is all about putting money to work to maximize risk-adjusted returns.
Robo-advisors are gathering small pools of money from households that aren’t investing now (so-called “mass affluent” households) and eliciting cash off the sidelines at a scale that previously wasn’t really possible when dealing with conventional money managers. On that level, it’s good for money flow because it sweeps these little pockets of cash and pours them into the market.
As these products expand, they’ll provide incremental support for the market as a whole, just like the dawn of retail mutual funds helped feed middle-class money into Wall Street. So, that’s good news for everyone.
Why Human Advisors Are Still Better
But, there are a few reasons why humans can still trump the machines. First, at some point, the AI’s strategy degenerates into momentum chasing; money will flow into better-performing stocks at a greater rate as they rise in price and see higher demand. This strategy works well in bull markets and shorter-term trading, and is likely contributing to the strength of FANG stocks right now — Facebook (FB), Apple (AAPL), Netflix (NFLX) and Alphabet (GOOGL, GOOG). But, when the bullish trend unwinds, as it did in 2000, the result is ugly for investors who aren’t prepared to adapt.
Second, robo-investing cannot identify bubbles. Programs still have retirees put 70% of their assets in bonds, despite the limited returns bonds have to offer. Again, when the rubber band snaps, it causes a lot of pain.
One advantage of human advisors is that they can offer different forms of scale and flexibility. I can pursue more nimble and responsive strategies than a typical robo-advisor because I don’t need every trade to be tailored to fit a massive $10 billion pool of capital, or a quarter-to-quarter investment policy statement. Human advisors can get a little smaller and a little more obscure, trading fleeting profit situations that pop open and snap closed before the automated platforms can even identify the opportunity.
Plus, we can be contrarian when it suits us, trading against the index. That’s the definition of alpha, which is how well a portfolio outperforms the market by reducing positions in some names while concentrating on others. For example, I was out of oil two years ago. Index funds and the robots they support are still obligated to maintain market weight on all of these stocks, so they buy Exxon Mobil (XOM), for instance, even though the company will probably remain dead money for months.
Some years, it could be that the passive, reactionary strategy of robots outperforms aggressive, active human trading. But, financial advisors can earn their keep, and then some, in the years the markets retreat. Better long-term return potential with less volatility is active investing’s trump card — and there will always be elements of investing that robots cannot predict.
It’s important to remember that every robot is only as good as the human expertise it’s been programmed to emulate.
Hilary Kramer is the editor of GameChangers, Breakout Stocks Under $10, High Octane Trader, Absolute Capital Return and Value Authority. She is an accomplished investment specialist and market strategist with more than 25 years of experience in portfolio management, equity research, trading, and risk management. She has extensive expertise in global financial management, asset allocation, investment banking and private equity ventures, and is regularly sought after to provide her analysis on Bloomberg, CNBC, Fox Business Network and other media.