By Michael Tierney, September 27, 2021
Using a mathematical model to guide one’s portfolio investment decisions has a record of success and a gain in popularity that correlates almost perfectly with the growth of the computational capacity we have at our fingertips. As computers have been able to handle exponentially growing amounts of data across an increasingly wide variety of sources, modeling to inform portfolios has recently led to some of the greatest investment records in history. James Simons for example, a mathematician who formed Renaissance Technologies to use algorithms to harness big data in computer models has, since its inception in 1988, produced the greatest record of investment success in the history of modern finance. No one in the investment world comes close. Warren Buffet, George Soros, Peter Lynch, and Ray Dalio to name a few greats, all fall short.
Model investing as described here is not to be confused with High Frequency Trading (HFT). HFT also uses powerful computers but the similarities to model investing end there. Securities trading in HFT is conducted by computer networks with the speediest high-speed connections to the various exchanges. HFT traders use their speed advantage in many cases to try to front-run institutional order flow. Simplified; HFT traders try to buy on the bid of a security and sell on the offer price. Their net profit per trade is often less than a penny, but they use the enormous computer capacity to trade many, many millions of shares per day – the fractions of pennies add up. HFT programs are by far the largest volume trade investors in the marketplace. Is it legal? It seems close to the line but ultimately that answer is for market regulators to decide.
The extraordinary success of Simon’s mathematical models and algorithmic trading programs has spawned an entire new industry. Outside of HFT, algo-trading represents the next largest category of daily trading volume on U.S. exchanges. It has become incredibly widespread in a very short period. Beware, however, the expression “model investing” is one of the most overused terms in finance today. Caveat emptor and due diligence are important components to investing in model driven strategies.
Algorithmic trading models are not a panacea for investment success. Investing is hard, it is difficult to consistently outperform the market, and it is no surprise that many model investment programs have underperformed their targeted benchmarks. But the spectacular success of some does point the initiated in an interesting direction. The reasons to invest under an open, rules-based model methodology are numerous. There is consistency and predictability, the avoidance of myopia, and most importantly, it removes emotion from the investment process and allows the investor to overcome behavioral biases. Furthermore, some model structures are tax advantaged for taxable accounts, and many have an exceedingly low fee structure overall.
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