Categories
đŸ–€ 💰

“The Man Who Solved the Market”; Gregory Zuckerman

Albert Einstein argued that there is a natural order in the world; There is true beauty to their work, especially when it succeeds in revealing something about the universe’s natural order.

Simons came from a different world and enjoyed a unique perspective. He was accustomed to scrutinizing large data sets and detecting order where others saw randomness. Scientists and mathematicians are trained to dig below the surface of the chaotic, natural world to search for unexpected simplicity, structure, and even beauty

Renaissance has been scoring over $7 billion annually in trading gains. That’s more than the annual revenues of brand-name corporations including Under Armour, Levi Strauss, Hasbro, and Hyatt Hotels. Here’s the absurb thing—while those other companies have tens of thousands of employees, there are just three hundred or so at Renaissance. Simons is worth about $23 billion, making him wealthier than Elon Musk of Tesla Motors, Rupert Murdoch of News Corp, and Laurene Powell Jobs, Steve Jobs’s widow.


1977: Jim in Stony Brook, but spent some time trading currency market for a fund by Shaio.

1978: Jim left academic and started his investment firm on currency trading, called Monemetrics, together with Lenny Baum. Baum would share in the 25 percent cut the firm claimed from all its trading profits. Simons failed to raise the $4 million he was shooting for, but he came close enough to begin his fund. Investors include Jimmy Mayer, Edmundo Eswuenazi. Jim setup Limroy as hedge fund.

James Ax and Hullender joined very soon.

Greg Hullender was offered $9,000 a year, as well as a share of his firm’s profits, to come to New York to program Limroy’s trades.

“Piggy Basket.” The group built it to digest masses of data and make trading recommendations using the tools of linear algebra. They closed out his potato positions, costing. Soon, he and Baum had lost confidence in their system. They could see the Piggy Basket’s trades and were aware when it made and lost money, but Simons and Baum weren’t sure why the model was making its trading decisions.

1979: Baum’s penchant for holding on to investments eventually caused a rift with Simons. The tension started back in the fall of 1979 for a Gold & Coffee lesson.

1980: Hullender quitted. With Hullender gone and the Piggy Basket malfunctioning, Simons and Baum drifted from predictive mathematical models to a more traditional trading style. They began looking for undervalued investments.

the spring of 1980, as Hullender prepared to leave Monemetrics, Ax recommended the firm hire Sandor Straus from Stony Brook as its new computer specialist.

1982: Renaissauce Technologies

1983: A sad denouement to a decades-long relationship between Simon and Baum. By then, Baum was trading for himself. As he grew older, Baum focused on prime numbers and an unsolved and well-known problem, the Riemann hypothesis.

1984: Baum quitted; he focused on prime number and Riemaun Hypothesis.

Searching for additional help, Simons asked Henry Laufer, a well-regarded Stony Brook mathematician, to spend one day a week helping out.

1985: James Ax established Axcom with Straus, with Jim sharing 25% . Axcom had been employing various approaches to using their pricing data to trade, including relying on breakout signals. They also used simple linear regressions, incorporating higher dimensional kernel regression approaches for trending models.

Elwyn Berlekamp, a game theorist

1987: Axcom had scored double-digit returns, sidestepping a crash in October that sent the Dow Jones Industrial Average plummeting 22.6 percent in a day.

1988: Jim closed Limroy and set up Medallion Fund with James Ax.

1989: James Ax leaves, Berlekamp bought Ax’s shares to lead Medallion. Berlekamp owned 40%, Jim and Straus 25%, and Ax 10%.

late 1989 with the $27 million Simons still managed. The results were almost immediate, startling nearly everyone in the office. They did more trading than ever, cutting Medallion’s average holding time to just a day and a half from a week and a half, scoring profits almost every day.

1990: Medallion scored a gain of 55.9 percent in 1990, a dramatic improvement on its 4 percent loss the previous year.

Jim bought Berlekamp’s ownership by cash, while Straus and Ax traded their Axcom stakes for shares in Renaissance. Berlekamp started Berkeley Quantitative, which did its own trading of futures contracts and, at one point, managed over $200 million. It closed in 2012 after recording middling returns.

1996: Jim’s son died.

Frey and Simon formed Kepler Financial

Melvin, David Magerman, Nick Patterson

1992: Henry Laufer join

1993: Peter Brown, Robert Mercer.

2006: James Ax died.

2012: Berkeley Quant closed

2016: Robert Mercer, who is perhaps the individual most responsible for Donald Trump’s presidential victory in 2016. Mercer, Trump’s biggest financial supporter. Companies formerly owned by Mercer and now in the hands of his daughter Rebekah played key roles in the successful campaign to encourage the United Kingdom to leave the European Union.

2017: Baum passed away at the age of eighty-six.

2019, Berlekamp died from complications of pulmonary fibrosis at the age of seventy-eight


“There are patterns in the market,” Simons told a colleague. “I know we can find them.”

Do what you like in life, not what you feel you ‘should’ do,”

“I had no interest in business, which is not to say I had no interest in money.”

Bad ideas is good, good ideas is terrific, no ideas is terrible.”

Albert Einstein argued that there is a natural order in the world; There is true beauty to their work, especially when it succeeds in revealing something about the universe’s natural order.

Some investors and academics saw the markets’ zigs and zags as random, arguing that all possible information was already baked into prices, so only news, which is impossible to predict, could push prices higher or lower

Simons came from a different world and enjoyed a unique perspective. He was accustomed to scrutinizing large data sets and detecting order where others saw randomness. Scientists and mathematicians are trained to dig below the surface of the chaotic, natural world to search for unexpected simplicity, structure, and even beauty.

It looks like there’s some structure here,

Truth . . . is much too complicated to allow for anything but approximations.John von Neumann

sports was overemphasized in society

it was a game in which rich people play around with each other, and it doesn’t do the world much good.

much of human interaction is colored by shades of gray that he sometimes found difficult to discern. Mathematics, by contrast, elicits objective, unbiased answers, results he found calming and reassuring. Truth in life is broad and nuanced; you can make all kinds of arguments, such as whether a president or person is fantastic or awful,” he says. “That’s why I love math problems—they have clear answers

When the boss isn’t present, the dynamics aren’t the same.


Markov Model: Markov chains, which are sequences of events in which the probability of what happens next depends only on the current state, not past event.

Laufer would buy futures contracts if they opened at unusually low prices compared with their previous closing price, and sell if prices began the day much higher

Berlekamp came to see the similarities between betting on horses and investing in stocks, given that chance plays a huge role in both. sized wagers can provide one with an advantage.

Stochastic Differential Equations

Simons and his colleagues ignored the basic information most investors focus on, such as earnings, dividends, and corporate news, what the code breakers termed the “fundamental economic statistics of the market.” Instead, 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 as “high variance,” when stocks experienced larger-than-average moves, and “good,” when shares generally rose. They used mathematics to determine the set of states best fitting the observed pricing data; their model thenmade its bets accordingly. The whys didn’t matter.

Factor investing, the use of models based on unobservable states, and other forms of quantitative investing—that would sweep the investing world decades later.

He valued “killers,” those with a single-minded focus who wouldn’t quit on a math problem until arriving at a solution.

Simple linear regression

If you trade a lot, you only need to be right 51 percent of the time,” Berlekamp argued to a colleague. “We need a smaller edge on each trade.”

Laufer discovered certain recurring trading sequences based on the day of the week. Monday’s price action often followed Friday’s, for example, while Tuesday saw reversions to earlier trends. Laufer also uncovered how the previous day’s trading often can predict the next day’s activity, something he termed the twenty-four-hour effect. The Medallion model began to buy late in the day on a Friday if a clear up-trend existed, for instance, and then sell early Monday, taking advantage of what they called the weekend effect.

e efficient market hypothesis.

Michael Milken. Martin Siegel, Ivan Boesky, Gordon Gecko,

Charles Dow,

The Money Game, the classic finance book of the period, author George Goodman

Munehisa Homma, argued that markets are governed by emotions

Kernal method; Higher dimensional kernal regression approaches worked best for trending models

Breakout, chased price, trend

Axcom’s model usually focused on two simple and commonplace trading strategies. Sometimes, it chased prices, or bought various commodities that were moving higher or lower on the assumption that the trend would continue. Carmona’s kernel methods—the early, machine-learning strategy that had made Simons so uncomfortable. Berlekamp suggested they should buy and sell larger amounts when their model suggested a better chance of making money,

Efficient Market Hypothesis

Morgan Stanley’s Quant: APT – Tartarglia, Frey

Laufer invest based on market conditions, not price actions, e.g. interest rate, disease, etc. It’s psychology.

Richard Dennis: turtle trader

Benjamin Graham and David Dodd’s landmark tome, Security Analysis

Peter Lynch, Jeffrey Vinik, Bill Gross Pimco