How to Use AI to Beat the Market

In the new book The Man Who Solved the Market: How Jim Simons Launched the Quant Revolution, Gregory Zuckerman tells the fascinating story of the rise of Simons and his investment company, Renaissance Technologies. Keep in mind that its flagship fund — called Medallion — has racked up average annual returns of 66% since 1988. This performance has beat other legendary investors like Steven Cohen, George Soros, Peter Lynch and Ray Dalio. In fact, Medallion’s gains have amount to a staggering $100 billion!

How to Use AI to Beat the Market
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How did Simons pull this off? Well, it was not about hiring smart investors. Instead, Simons mostly hired mathematicians, physicists and computer scientists (by the way, he started his career as a prominent mathematician). And they would create sophisticated artificial intelligence (AI) models that used sophisticated approaches like Markov chains, Baum-Welch algorithms and stochastic equations.

Thus, by crunching huge amounts of data and engaging in short-term trading, Simons’ team was able to essentially beat the stock market in a big way.

No doubt, Wall Street has taken notice — and is focused on finding ways to leverage AI. However, it has been very challenging. Note that Renaissance Technologies is highly secretive and has its employees sign 30-page nondisclosure agreements.

Despite this, there are more and more examples of how AI is transforming the investment world.

Changing the World Of Stock Market Analysts

Morgan Stanley (NYSE:MS) recently published a report on a sophisticated AI project that focused on more than 41,000 research reports from its own analysts. By using sophisticated deep learning algorithms, patterns emerged that showed when a report was truly bullish or not. Hey, as is common, analysts do not like to come out and put “sell” signals on stocks.

But for AI, this does not matter. The technology can read the true intentions. The bottom line: When looking at bullish sentiment, the stocks performed 9.6% better than the average. This was back-tested from January 2013 to May 2019.

Another example to consider of the power of AI is from Morningstar (NASDAQ:MORN). The company had been struggling to cover the large number of mutual funds and exchange-traded funds (ETFs). So MORN spent four years building an AI model to essentially replicate the actions of its analysts. To do this, the company used the “random forest” algorithm and regression. The data was back-tested for 14 years and, for the most part, the results were in-line what the analysts would have used for the ratings.

AI-Driven ETFs

Okay, then, what about AI-driven investment vehicles for retail investors? There are definitely some interesting offerings available, such as the AI Powered Equity ETF (NYSEARCA:AIEQ). It is powered by IBM’s (NYSE:IBM) Watson platform and mimics the work of 1,000 research analysts (who, by the way, don’t work 24/7).

According to the fund’s prospectus: “Each day, 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 125 companies with the greatest potential over the next 12 months for appreciation and their corresponding weights, while maintaining volatility (i.e., the range in which the portfolio’s returns vary) comparable to the broader U.S. equity market.”

Currently, among the portfolio’s 132 holdings, the top stocks include Alphabet (NASDAQ:GOOGL), Intuit (NASDAQ:INTU), and Amazon (NASDAQ:AMZN).

Similarly, there’s the AI Powered International Equity ETF (NYSEARCA:AIIQ). It also uses the Equbot/Watson tools, but that’s pretty much where the similarities end. Its more-global portfolio of 154 stocks share very few of the top 20 names in AIEQ’s holdings. Instead, investors will find names like Brookfield Asset Management (NYSE:BAM) and Toyota Motor (NYSE:TM).

What about the performance of the AIEQ and AIIQ ETFs? While they’ve only been around since October 2017 and June 2018, respectively, for 2019 so far, both funds are up about 26% (by the way, MORN’s AI-based rating is “Negative”).

Then again, when it comes to the availability of AI for retail investors, it’s still early days. But given the advances and innovations in the industry, expect more investment options to emerge in the coming years.

Tom Taulli is the author of the book, Artificial Intelligence Basics: A Non-Technical IntroductionFollow him on Twitter at @ttaulli. As of this writing, he did not hold a position in any of the aforementioned securities.

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