Are Quant Funds In Deep Water?

Quant funds have always had an allure when it comes to trading and investing because computers appear to take out the fallible human element. However, these funds are based on the presumption that a pattern will recur. When that does not happen, problems arise. This is due to a number of factors across a diverse range of quantitative trade types.

We witnessed this last November, when two major quantitative investment management giants struggled to keep up with a volatile and unpredictable market due to the months-long COVID-19 pandemic. The respiratory disease spread across the globe, negatively impacting the economies of numerous countries.

Long Island, New York-based Renaissance Technologies, known as one of the most successful and secretive hedge funds in the world, experienced a substantial loss of about 20 percent in October. The company’s market-neutral fund, valued at $75 billion, declined approximately 27 percent, while its global equities fund dropped 25 percent. 

New York City-based hedge fund Two Sigma Investments also had a rough year, experiencing an annual loss of 11.5 percent as of November. Valued at $58 billion, the company’s absolute return fund dropped 2.7 percent, with its absolute return macro shrinking by 23 percent. 

The Disadvantages of Quant Firms

Although the COVID-19 pandemic was partially to blame for the unpredictability of last year’s market, the significant losses experienced by Two Sigma and Renaissance raised some important questions: What are quant firms doing wrong? Why are they failing to adapt to unforeseen market conditions? Can we no longer rely on mathematical models, computer-generated analyses, and automated algorithms to predict successful trades? Why are these tried-and-true investment models struggling in an unstable market? 

Many algorithmic funds understand how to exploit recurring patterns in the marketplace in order to make money, but they fail to understand why the pattern occurs in the first place. Some, like Renaissance, hire employees with no prior financial education, background, or training. These computer scientists, mathematicians, physicists, and statisticians rely solely on computer-automated technology to initiate trades and predict price fluctuations. That may work in a more orderly market, but too much dependence on artificial intelligence can backfire if the market trend turns volatile.

Skilled Traders Are Becoming Rare Commodities

Successful, versatile traders are like Jedi Masters in Star Wars—a dying and diminishing breed. Unlike artificial intelligence, which uses statistics, algorithms, or mathematical models and is unfailingly predictable, the best traders harness their human knowledge, intuition, and judgment to adapt quickly in the face of erratic or unstable market conditions. This is something quant firms—with even the best mathematicians, physicists, and computer scientists at the top of their respective fields—are not well equipped to do. Successful traders want to know what drives lucrative trades. This scarce form of curiosity gives them the ability to react quickly if and when market conditions change. 

Shrouded in Secrecy

Traditional hedge funds make money by taking a percentage of investors’ earnings—typically about 2 percent of the total amount of assets managed, plus 20 percent of profits that go above a certain benchmark. This strategy works out well, until they have a year of losses that earns them nothing. Additionally, the traditional model means they won’t earn another penny until they’ve made up for the losses. Because of this, years of excellent returns followed by just one year of losses will cause hedge funds to collapse. This is why we should be critical of traditional hedge firm structures. 

Many quant funds refrain from revealing the secrets of their trades. Transactions are carried out based on analyses or algorithms with little to no input from actual traders. From an investor’s perspective, how can you divest yourself from a fund if you don’t truly understand its weaknesses? Algorithmic funds typically use strategies that have backtested well, but if and when the market changes, methods that have performed well in the past are much less likely to work well in the new environment. 

Failure to Understand Profit and Loss

For years, many quant firms have operated on an unspoken principle: It didn’t matter why they were making money, as long as they were making it. But if you don’t understand your victories, how can you acknowledge your failures? More importantly, how can you prevent them from happening again? 

Quant funds often claim they’re not interested in what factors drive their profits and losses—they simply look for trades that perform well. This method is short-sighted and makes them less likely to recognize when trades may suffer. This is why many quant funds are left with a profit-and-loss profile that resembles a highly leveraged retail trader. Yes, they can make money in calm, predictable, trending conditions, but a volatile market could lead to financial disaster. Making money in upward market conditions is easy, but truly exceptional traders thrive even in highly volatile or erratic market conditions.

Quantitative firms will continue to struggle if they’re unwilling to delve deeper into their shortcomings. As we witnessed in 2020, even financial powerhouses Two Sigma and Renaissance were not immune to the dramatic fluctuations of an unstable market, which led to significant loss. The skills of a trader are necessary during difficult market conditions—a fact that quant investors are learning the hard way. 

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Peter Davies is CEO & Founder of Jigsaw Trading. Davies is an active order flow trader in S&P 500 futures who founded Jigsaw in 2010 because he was frustrated with the modern trading platforms available to investors and was on a mission to create tools that presented order flow information in a more logical and understandable way. Jigsaw Trading offers investors unique analytical trading tools and software to monitor order flow in global futures markets.

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