Mathematicians and data scientists anticipate panic on Wall Street better than economists

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– “Where are you at?”a trader asked John Meriwether, founder of the investment fund Long Term Capital Management.

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– “50% off”replied the financier.

– “You did. The market will smell you and eat you.”answered the operator in the best style Dibu Martínez.

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So it was. In a couple of months on Wall Street in 1998, Meriwether and her partners would lose $2 billion in personal fortunes. The Fed bailed out the fund as a firewall for the US financial system.

LTCM has had in its ranks none other than economists Robert Merton and Myron Scholes, awarded only a year ago with the Nobel Prize in Economics for the model they used to value stocks. By compiling historical data on asset valuations and computerizing their operations, they earned an annual average of 50% dollars over three years and were left with $7 billion in 1997 alone.

So what went wrong with LTCM? The model wasn’t prepared for a shock like Russia’s default, losing more than $35 million in a wheel (it turned out to be $553 million down one day), and, a fact though it may not be so much, in its ranks were almost all economists.

“We build models that are used by Wall Street to manage portfolios. They analyze risks and are optimization engines to accelerate decisions efficiently and simultaneously”

"We build models that are used by Wall Street to manage portfolios. They analyze risks and are optimization engines to accelerate decisions efficiently and simultaneously"
Sebastian Ceria
Argentine mathematician, philanthropist and president of Fundar, a public policy think tank

This is how the publisher of The Wall Street JournalGregory Zuckerman, in his book The man who fixed the market about the life and work of Jim Simons, an academic, mathematician, Wall Street investor and philanthropist, who made more money than Warren Buffet and George Soros. An American, Simons founded Renaissance Technologies in the 1980s, and within that company he launched the first fund (Medallion) that used large-scale quantitative modeling to trade and make investments.

“Renaissance hired mathematicians and data scientists, not economists like LTCM”. This and the dialogue at the top of the column (by Meriwehter) are in Zuckerman’s book.

“I don’t wonder why the planets orbit the sun”, Simons argues that he argues why we shouldn’t waste time trying to give economistic explanations to the phenomena. Markets have models and “Just because I don’t understand them doesn’t mean I can’t predict them”.

The MIT mathematician and his team have deliberately ignored basic information that investors have dissected such as earnings, dividends, financial news, and whatever programmers or codebreakers call “fundamental” or fundamental economic statistics. Instead, they collected smaller numbers, delving into macroscopic variables that can predict immediate market behavior. If Marcelo Bielsa said there were between 12 and 15 chances to reach goal and ball paths, Simons and his team argued that the market had something like this: eight states, from the most volatile to the most stable. It was all about spotting signals that can provide enough information to predict price movements and schedule. This method is called quantitative and I bet the data speaks for itself.

Simons’ fund (Medallion) gained 74% in 1994, the year of Tequila, just as the Fed surprised investors by raising rates and leading to a loss of wealth not seen since the fall of the Wall. And he made most of his money in times of extraordinary turmoil. Perhaps thanks to what the Nobel Prize winners for Economics, Amos Tversky and Daniel Kahneman had demonstrated (that investors and people overreact in stressful situations, making emotional decisions and acting irrationally in investment matters), “Humans are more predictable in times of stress, acting instinctively and with panic. We’ve learned to take advantage of that,” Simons said.

The quantitative method was actually used before the Great Depression. The American engineer and statistician Roger Babson warned in September 1929 that “sooner or later there will be a crash on Wall Street.” Babson had developed a prediction method based on Isaac Newton’s third law (motion). Babson became an economist, but he had an engineering degree and his predictions proved to be more accurate than those of economists such as Yale professor Irving Fischer and John Maynard Keynes of Cambridge.

Sebastián Ceria, Argentine mathematician, philanthropist and president of Fundar, a public policy think tank, created a company in 1998 (Axioma) that builds the current models used by the Wall Street wolves to manage their portfolios. “They analyze risk and are optimization engines to accelerate decisions efficiently and simultaneously,” he explained to Económico while passing through Argentina this week. In 2019, Axioma was sold for $850 million on the German Stock Exchange and merged with Stoxx to create the new company of which Ceria is now CEO: Qontigo (based in New York). The one that refers to the quantitative method of Simons.

Source: Clarin

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