The stock market appears strangely indifferent to Covid-19 these days, but that wasn't true in March, as the scale and breadth of the crisis hit home. By one measure, it was the most volatile month in stock market history; on March 16, the Dow Jones average fell almost 13 percent, its biggest one-day decline since 1987. To some, the vertigo-inducing episode also exposed a weakness of quantitative (or quant) trading firms, which rely on mathematical models, including artificial intelligence, to make trading decisions. Some prominent quant firms fared particularly badly in March. By mid-month, some Bridgewater Associates funds had fallen 21 percent for the year to that point, according to a statement posted by the company's co-chairman, Ray Dalio. Vallance, a quant fund run by DE Shaw, reportedly lost 9 percent through March 24.

The stock market appears strangely indifferent to Covid-19 these days, but that wasn't true in March, as the scale and breadth of the crisis hit home. By one measure, it was the most volatile month in stock market history; on March 16, the Dow Jones average fell almost 13 percent, its biggest one-day decline since 1987. To some, the vertigo-inducing episode also exposed a weakness of quantitative (or quant) trading firms, which rely on mathematical models, including artificial intelligence, to make trading decisions. Some prominent quant firms fared particularly badly in March. By mid-month, some Bridgewater Associates funds had fallen 21 percent for the year to that point, according to a statement posted by the company's co-chairman, Ray Dalio. Vallance, a quant fund run by DE Shaw, reportedly lost 9 percent through March 24.

FIFTY YEARS ago investing was a distinctly human affair. "People would have to take each other out, and dealers would entertain fund managers, and no one would know what the prices were," says Ray Dalio, who worked on the trading floor of the New York Stock Exchange (NYSE) in the early 1970s before founding Bridgewater Associates, now the world's largest hedge fund. Kenneth Jacobs, the boss of Lazard, an investment bank, remembers using a pocket calculator to analyse figures gleaned from company reports. His older colleagues used slide rules. Even by the 1980s "reading the Wall Street Journal on your way into work, a television on the trading floor and a ticker tape" offered a significant information advantage, recalls one investor. Since then the role humans play in trading has diminished rapidly. In their place have come computers, algorithms and passive managers--institutions which offer an index fund that holds a basket of shares to match the return of the stockmarket, or sectors of it, rather than trying to beat it (see chart 1).

Hedge funds that use artificial intelligence and machine learning in their trading process posted the worst month on record in February, according to a Eurekahedge index that's tracked the industry from 2011. The first equity correction in two years upended their strategies as once-reliable cross-asset correlations shifted. While computerized programs are feared for their potential to render human traders obsolete, the AI quants lagged behind their discretionary counterparts. The AI index fell 7.3 percent last month, compared to a 2.4 percent decline for the broader Hedge Fund Research index. The slump even surpassed a more traditional category of quants, commodity trading advisers or CTAs, which posted near-record losses as the equity reversal hammered the automated trend-following strategies.

The value that can be extracted from a growing wealth of data across boundless sectors is only just beginning to be grasped. If you look at search engines or digital commerce platforms, an almost direct relationship exists between the amount of data users willingly give up and the value this has. There is also the fact that those with the most data at their disposal will probably have the best artificial intelligence in the future, making them nigh on invincible. In finance, data of one sort or another has always held intrinsic value. People who trade in the zero-sum game of capital markets all need a Bloomberg terminal or Thomson Reuters data to have a look at all the traditional price information, earnings estimates and so on.

Hedge funds focused on artificial intelligence and machine learning as tools for investment have long been viewed as the future of the industry by many analysts. However, the figures from February paint a picture that is far less optimistic. A recent report by Bloomberg, citing information by Eurekahedge, reveals that this group of hedge funds saw its worst month on record in February. The poor performance was tied with the first equity correction in about two years, meaning that cross-asset correlations shifted, overturning the AI strategies which were usually seen as reliable indicators of market movement. The Hedge Fund Research index, tracking all discretionary funds, posted a 2.4% decline for February.

The use of Artificial Intelligence as an investing tool was once reserved for the top of the Wall Street food chain. Only the largest commercial traders, financial institutions, hedge funds, and others with the necessary resources could implement an AI-based trading strategy into their portfolios. But as Bob Dylan said, 'the times they are a-changin'. Today you'd be hard-pressed to find any financial institution, regardless of size or capital, that isn't utilizing AI in some way to inform how they trade. AI's influence over Wall Street has grown exponentially in the last decade, and as that's happened, the barrier to entry for individual traders to benefit from the power of AI has been lowered.

Quant funds are expected to account for US$1 trillion in assets this year. But when algorithms are managing this money, who manages the algorithms? Computer-powered, data-driven strategies have continued their spectacular march towards dominating the hedge fund industry. According to research by HFR, the amount of money being managed by quant hedge funds rose to more than $940 billion by the end of October 2017 and is on course to pass the $1 trillion at some point this year. This is an enormous amount of money being managed by machines.

The value that can be extracted from a growing wealth of data across boundless sectors is only just beginning to be grasped. If you look at search engines or digital commerce platforms, an almost direct relationship exists between the amount of data users willingly give up and the value this has. There is also the fact that those with the most data at their disposal will probably have the best artificial intelligence in the future, making them nigh on invincible. In finance, data of one sort or another has always held intrinsic value. People who trade in the zero-sum game of capital markets all need a Bloomberg terminal or Thomson Reuters data to have a look at all the traditional price information, earnings estimates and so on.

Such softwares reduce or totally eliminate the need for human intervention in the investing or trading process that is present in the traditional human discretional approach through fund managers and brokers. CPG is one of the few quant fund operators in Singapore today with total assets under management at slightly below US$100mil (RM434mil). Locally, BIMB Investment Management Bhd, which is a unit of Bank Islam Malaysia Bhd, recently launched its fund using AI technology. Whether or not quant funds outperform the traditional discretionary approach of investing is still very much open to debate.