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October 12 - October 18, 2021
A former math professor, Simons is arguably the most successful trader in the history of modern finance. Since 1988, Renaissance’s flagship Medallion hedge fund has generated average annual returns of 66 percent, racking up trading profits of more than $100 billion (see Appendix 1 for how I arrive at these numbers). No one in the investment world comes close. Warren Buffett, George Soros, Peter Lynch, Steve Cohen, and Ray Dalio all fall short
Robert Mercer, who is perhaps the individual most responsible for Donald Trump’s presidential victory in 2016. Mercer, Trump’s biggest financial supporter, plucked Steve Bannon and Kellyanne Conway from obscurity and inserted them into the Trump campaign, stabilizing it during a difficult period.
“The lesson was: Do what you like in life, not what you feel you ‘should’ do,” Simons says.
“Reconstruction had left them as tenant farmers, but it was the same as slavery,”
The IDA taught Simons how to develop mathematical models to discern and interpret patterns in seemingly meaningless data. He began using statistical analysis and probability theory, mathematical tools that would influence his work.
Differential equations—which are used in physics, biology, finance, sociology, and many other fields—describe the derivatives of mathematical quantities, or their relative rates of change.
Simons created a partial differential equation of his own, which became known as the Simons equation, and used it to develop a uniform solution through six dimensions.
In 1968, Simons published “Minimal Varieties in Riemannian Manifolds,”
they proposed searching for a small number of “macroscopic variables” capable of predicting the market’s short-term behavior. They posited that the market had as many as eight underlying “states”—such
relying on a sophisticated mathematical tool called a hidden Markov model.
Harry Markowitz, the University of Chicago Nobel laureate and father of modern portfolio theory, was searching for anomalies in securities prices, as was mathematician Edward Thorp. Thorp would attempt an early form of computerized trading, gaining a head start on Simons.
The Baum-Welch algorithm provided a way to estimate probabilities and parameters within these complex sequences with little more information than the output of the processes.
In a Markov chain, each step along the way is impossible to predict with certainty, but future steps can be predicted with some degree of accuracy if one relies on a capable model.
Members of Axcom’s team viewed investing through a math prism and understood financial markets to be complicated and evolving, with behavior that is difficult to predict, at least over long stretches—just like a stochastic process.
linear regressions, a basic forecasting tool relied upon by many investors that analyzes the relationships between two sets of data or variables under the assumption those relationships will remain linear.
Berlekamp held a dismissive view of finance. “My impression was that it was a game in which rich people play around with each other, and it doesn’t do the world much good,”
The roots of Simons’s investing style reached as far back as Babylonian times, when early traders recorded the prices of barley, dates, and other crops on clay tablets, hoping to forecast future moves. In the middle of the sixteenth century, a trader in Nuremberg, Germany, named Christopher Kurz won acclaim for his supposed ability to forecast twenty-day prices of cinnamon, pepper, and other spices.
David Leinweber later would determine that US stock returns can be predicted with 99 percent accuracy by combining data for the annual butter production in Bangladesh, US cheese production, and the population of sheep in Bangladesh and the US.
Some of Mercer’s comments were downright abhorrent. Once, Magerman recalls, Mercer tried to quantify how much money the government spent on African Americans in criminal prosecution, schooling, welfare payments, and more, and whether the money could be used, instead, to encourage a return to Africa.
By analyzing and estimating hundreds of financial metrics, social media feeds, barometers of online traffic, and pretty much anything that can be quantified and tested, they uncovered new factors, some borderline impossible for most to appreciate.
“Even a smart guy can get the details right but the big picture wrong.”
In March 2012, Breitbart collapsed on a Los Angeles sidewalk and died of heart failure at the age of forty-three. Bannon and the Mercers convened an emergency meeting in New York to determine the network’s future, and decided that Bannon would become the site’s executive chairman.
“Brexit could not have happened without Breitbart,” Farage says.
Bannon helped instill order on the campaign, making sure Trump focused on two things—disparaging Clinton’s character and promoting a form of nationalism that Bannon branded “America First,” a slogan that seemed to echo the short-lived America First Committee, a group that had levied pressure to prevent the US from entering World War II and opposing Adolf Hitler.
Mercer sent Magerman a book called Civil Rights: Rhetoric or Reality? written in 1984 by Hoover Institution economist Thomas Sowell
The book argues that minorities began moving into higher-paying jobs in large numbers years before the passage of the Civil Rights Act, and that affirmative action had caused the most disadvantaged segments of the minority population to fall behind their white counterparts.
Mercer served notice that she would continue to push to limit the role of government and make sure politicians emphasized “personal responsibility.”
Today, even banking giant JPMorgan Chase puts hundreds of its new investment bankers and investment professionals through mandatory coding lessons.
