Will AI help investors beat the stock market? Don’t count on it.

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Other people may get excited about what AI means for the stock market or investing, but you can count me out.

This “exciting” new artificial intelligence technology may spark a juicy, profitable bubble that we can trade for a quick buck (thank you, NVIDIA! ) but there is every reason to question whether it will help regular investors outperform the market over time.

Not that this will stop people trying, of course.

Exhibit A for the prosecution here is the “AI Equity Powered ETF” an exchange-traded fund that has been heroically trying to use AI to beat the market for nearly six years. It was launched in 2017 by the ETF Managers Group of Summit, N.J., manages $115 million in investments, and is “definitely the most established” such AI fund on the market, according to Morningstar analyst Bryan Armour.

The fund uses IBM’s Watson artificial intelligence platform to analyze over 5,000 U.S. securities relentlessly, looking for winning angles. The fund picks stocks based on “a proprietary, quantitative model” developed by AI-focused technology company EquBot Inc., says ETF managers in the prospectus.

“Each day,” the firm says, “the EquBot Model ranks each company based on the probability of the company benefiting from current economic conditions, trends, and world events and identifies approximately 30 to 200 companies with the greatest potential over the next 12 months for appreciation and their corresponding weights, targeting a maximum risk adjusted return versus the broader U.S. equity market.” Phew!

The fund may invest in the securities of companies of any market capitalization, and “the model recommends a weight for each company based on its potential for appreciation and correlation to the other companies in the Fund’s portfolio.”

This AI platform, says the fund’s managers, is “equal to a team of 1,000 research analysts, traders and quants working around the clock.”


What chance do mere humans have?

So…how is it doing?

I’m glad you asked.

Since the launch in October 2017, AIEQ has underperformed the S&P 500 large-cap U.S. stock index, the total U.S. stock market, and even a strategy of investing blindly but equally in over 600 U.S. stocks—the equivalent of picking stocks by having 1,000 monkeys throw darts at a bunch of names on a wall. It has also underperformed the S&P 400 midcap stock index, and just kept up with the S&P 600 small cap index.

In numbers, since the launch the AI Powered Equity Fund has earned a total return of 41% according to FactSet data.

The State Street SPDR S&P 500 ETF over the same period: 88%.

The Vanguard Total Stock Market Index Fund or its ETF equivalent has earned 80%

Even the iShares MSCI U.S.A. Equal Weight ETF —the fund closest to picking stocks like a monkey with darts—is up 60%.

The AI powered fund has also trailed the SPDR S&P 400 midcap ETF by a full 10 percentage points.

The AI engine with the power of 1,000 analysts, traders and quants, “working around the clock,” didn’t even help AIEQ avoid the icebergs last year. The fund lost 32% in 2022.

That was nearly twice as much as the iShares MSCI U.S.A. Equal Weight ETF.

This performance required incredible amounts of trading, too. ETF Managers Group discloses that the ETF’s portfolio turnover last year was 1,708%—the equivalent of buying and selling every stock 17 times in the course of the year.

Management fees, at 0.75%, aren’t huge—but they are far more than those charged by index funds, which can be below 0.1%.

Chida Khatua, chief executive of Equbot, says the comparisons are misleading. The fund, he points out, scans over 5,000 securities, not just the large-caps in the S&P 500. Compared to the broadly based Russell 2000 small cap index it has stacked up much better, he points out.

He’s right, too. FactSet data show that since October, 2017 AIEQ has beaten the iShares Russell 2000 by 9 percentage points. (On the other hand it has trailed iShares Core S&P Small-Cap ETF which tracks the S&P 600, by small margin.)

AIEQ did much better during the boom up until November 2021, and has given back all that outperformance since.

 “The AIEQ strategy is not meant to replace the S&P 500 but to serve as a compliment in an investor’s portfolio,” Khatua says. “Historically, AIEQ has been a concentrated portfolio of (about) 140 companies, mostly mid and small cap,” he says. “AIEQ has done well when markets are rising and there is broad participation among market constituents and when mid and small cap names tend to lead the market higher. (But) this portfolio concentration also tends to create challenges when markets are in a downtrend.”

He adds that the AI model can be thrown by dramatic changes in economic direction. “The AI system is trained on past data, so when the system notices familiar market data environments the prediction can be more accurate,” Khatua says. “The reverse of this is also true such as unprecedented inflation and aggressive monetary policy,” such as since November, 2021.

It is also fair to point out that six years is still early stages. It will take a lot longer to give full tests both to this model, and AI-powered funds generally.

But the fund’s performance is a small key that opens a large door. Despite the inevitable high hopes, why should AI-powered equity funds ever outperform? Everyone will have access to the same data, and the same models. There are already untold legions of analysts, traders and quants poring over every inch of the market, backed by computers that are almost beyond the imagination of those living 30 years ago.

It’s true that AI-powered funds can now crunch the numbers on thousands of companies, including very small companies, that were once too small to merit an analyst’s time. But the market is a zero-sum game. If everyone around the poker table is a better player, that still doesn’t change the equation. They can’t all win. Since computers have transformed Wall Street, low-cost index funds have become a better deal, not a worse one. The computers, and the hedge funds, have vacuumed up all the little nickels that the inefficient markets had left lying around. There is little left to arbitrage away.

The best case scenario is that AI might stimulate more interest in small and very small (“micro”) cap stocks. The smart response is probably just to buy a regular small cap fund—or maybe just a small cap index fund, like or and enjoy any uplift on the cheap.

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