Stranger than that, Simons hired people who knew nothing about investing; Instead, Medallion’s employees were mathematicians and scientists like himself. While ordinary investors relied on economic intuition and instinct, consulting with executives and analyzing earnings reports to make trades, Simons took a different path to investing.

As a veteran mathematician, Simons believed that the market behaves rationally; So he decided to enter the field of capital with a scientific approach. He made decisions based on large sets of data, computer models, and algorithms, and inspired the revolution that swept Wall Street.

Jim Simons was never calm; It was not enough for him to be a mathematician, nor to be a professor at MIT and Harvard, nor to crack codes for the US National Security Agency during the Cold War. According to his first wife, Barbara Blustein, in The Man Who Solved the Market Riddle , “Jim learned from an early age that money equals power.”

Jim Simons, the pioneer of investing with computer models and known as the “Quant King”, died at the age of 86 on May 10, 2024 (May 21, 1403) in Manhattan, New York. This is the story of a mathematician who, with the help of mathematical magic and algorithms, produced the world’s biggest money-making machine in his mysterious company and became the biggest investor in history.

James Harris Simons , the only child of Matthew Simons and Marcia Kantor , was born on April 25, 1938 in Brookline, a suburb of Boston. His mother worked as a volunteer at Jamie’s school and saw the fulfillment of her own dreams in her son. Jimmy’s father was a sales representative for 20th Century Fox, but later worked in his father-in-law’s shoe factory. Matthew later told his son that he wished he hadn’t given up his promising career in the film industry for what was expected of him. The lesson Jimmy learned from his father was: “Do what you love, not what you feel you have to do.”

What Jimmy loved to do more than anything else was think about math. His mind was always occupied with numbers and shapes. At the age of three, he could multiply and divide numbers by two and knew all the powers of two up to the number 1024. At the age of four, when his father stopped for gas, Jimmy was pondering one of Xenon’s paradoxes , known as the two-part paradox.

At the age of eight, when the family doctor told Jamie that his ideal career would be medicine, Jamie replied, “I want to be a mathematician or a scientist.” The doctor insisted that there was no money in mathematics, but Jimmy said he didn’t care about money.

As he had hoped, Simons majored in mathematics at MIT, skipping his freshman year because of the advanced mathematics course he had taken in high school. With too much self-confidence, he decided to go to graduate abstract algebra in the second semester; But he could not keep up with his classmates. So he bought a book on abstract algebra and studied it all summer until he finally “bloomed,” as he put it.

The next year, when he came up with Stokes’ Theorem, a surprising combination of calculus, algebra, and geometry, he did so well in class that students sought his help. Simons was delighted to see that powerful theorems and formulas could reveal the secrets of truth and connect the disparate fields of mathematics and geometry. He said: “Mathematical concepts were beautiful and elegant to me.”

Simons earned a bachelor’s degree in mathematics after three years at MIT, and got his first taste of investing while studying for a doctorate at the University of California, Berkeley. He went to a brokerage in San Francisco to trade soy futures.

Read more: The biography of Pavel Durov

Simons returned to MIT in 1961 to teach, feeling that his future path was clear. In a 2020 interview with the American Institute of Physics, he said: “I remember one day I was sitting in the library and I said to myself, well, first I will become an assistant professor, then an assistant professor, and then a professor, and I will continue to live like this until I die. But at that moment I thought that maybe there are other things in the world.”

In 1963, Simons accepted a research position at Harvard University, teaching an advanced graduate course on partial differential equations. Simons didn’t know much about the subject, but he found teaching a good way to learn. He used to tell his students that he learned the subject a week or two before the class; A confession that was funny to the students.

A year later, Simons also left Harvard to join the IDA intelligence group to decipher coded messages from the Soviet Union during the Cold War. The Institute for Defense Analyzes was affiliated with the National Security Agency, which is the largest and most secret intelligence agency of the United States.

Starting at IDA, Simons’ salary doubled and he was able to clear his debts. In addition, he could pursue his own mathematical projects while collaborating with the government. The only problem with working at IDA was that he couldn’t tell anyone about his achievements, because everyone in the group was sworn to secrecy.

Simons joined the IDA during a turbulent period, as complex Soviet codes had not been systematically deciphered for more than a decade. However, working in an intelligence agency taught Simons how to build mathematical models to recognize and interpret patterns in seemingly meaningless data.

Jim Simons worked for the National Security Agency for more than three years before being fired for protesting the Vietnam War. In an article for the New York Times , Maxwell Taylor , the head of the IDA, asserted that the United States was about to win a war that was worth it. In a letter to the editor, Simons wrote that “any political gains from military victory cannot possibly offset its enormous economic, intellectual, and moral costs.”

Three days later, the US president announced the end of the bombing of Vietnam, which marked the end of the war. Simons assumed the news meant he could go back to work, but he was told not to bother going back.

While working at IDA, Jim Simons devoted his free time to studying the stock market. With the help of three other colleagues, he designed a new system for stock trading and claimed that their method can have at least 50% annual profit.

The unique feature of the Simons system was that it did not try to identify or predict different states of the stock market with economic theory or other conventional methods, and it did not seek to investigate why the market enters certain states.

Jim Simons and his colleagues also proposed a similar approach to forecast stock prices, relying on a complex mathematical tool called the “Hidden Markov Model”. Just as a gambler may infer the state of mind of an opponent based on his decisions, an investor may infer the state of the market from its price changes.

Simons’ argument was that it is not important to understand all the underlying levers of the stock market, but rather to find a mathematical system that matches these levers with the ability to make consistent returns. The Simons model was the forerunner of revolutions in the financial field; Including factor investing, the use of models based on unobservable states and other quantitative investment methods that swept the investment world decades later.

After being fired from IDA and at the age of 30, Simons managed to become the head of the mathematics department of Stony Brook University in New York with the suggestion of his mathematician friend. Simons made a discovery in Stony Brook about the reduction of shapes in curved and three-dimensional spaces. When he showed his discovery to the brilliant physicist Shiying-Shen Chern , Chern realized that the theory could apply to all dimensions, not just three-dimensional space. Chern and Simons introduced the Chern-Simons invariant constant in their 1974 paper “Characteristic Forms and Geometric Variables”, which was used in various mathematical fields.

In 1976, at the age of 37, Simons received the American Mathematical Society’s Oswald Veblen Prize in Geometry, the highest honor in the field, for his paper with Chern, as well as his earlier research on minimal manifolds. A decade later, theoretical physicist Edward Witten and others discovered that Chern-Simons theory has applications in a wide range of areas of physics, including dense matter, string theory , and supergravity. This theory was even critical to the methods used by companies like Microsoft to develop quantum computers capable of solving extremely complex problems, including drug development and artificial intelligence.

By 1977, Jim Simons was convinced that the currency markets were extremely profitable. World currencies were moving up and down regardless of the price of gold, and the British pound had fallen. According to Simons, a new era of instability had begun. In 1978, Simons finally left academia to start a small firm focused on currency trading; A decision that neither his father liked nor the mathematicians who knew him.

But Simons saw the story differently. By the age of forty, he had experienced a career in deciphering, had climbed the heights of mathematics, and had set up his own successful mathematics department. Now he was sure that he could conquer the trading world as well.

For centuries, investors have been trying to solve the mystery of the market and dominate it; But they rarely achieve great success. Some investors and analysts considered market fluctuations completely random and believed that all possible information was already included in the prices; So only events that are impossible to predict can make prices go up or down. But Simons came from the world of mathematics and was used to scrutinizing large sets of data and finding order and patterns where others saw only random occurrences.

Jim Simons concluded that the stock market does not always react logically and explainably to news or events, and that relying on traditional research makes it difficult to predict prices. However, prices seemed to show at least a few distinct patterns even in chaotic arithmetic markets.

Simons decided to treat the financial markets like a chaotic system. Just as physicists create beautiful models by analyzing large amounts of data to identify laws in nature, Simons wanted to create mathematical models to identify order in financial markets. His approach was very similar to the strategy he had devised years ago at IDA. At that time, Simons said that the markets are in various hidden states that can be revealed by mathematical models.

To test this strategy in the real world, Simons launched Monemetrics, an investment firm in Long Island, New York, later renamed Renaissance Technologies. Manometrics was derived from two words “Money” and “Econometrics”. Simons wanted to show that he could generate a lot of wealth by using math and analyzing financial data. So, instead of hiring an investor, he hired a team of mathematicians like himself to analyze market data for months, identify trends and write mathematical formulas to make money from the stock market.

One of these mathematicians who was willing to give up his lucrative job at IDA to make Simons’ dream come true was Leonard Baum , who had helped Simons write the IDA research paper. It didn’t take long for Baum to develop an algorithm for the Renaissance. If the value of the currency went below a certain level of the trend line, the algorithm said to buy it; And if it went above this line, it was time to sell. Baum, who until one or two years ago did not think about anything else except mathematics, now only thought about currency transactions.

Renaissance started its business with foreign exchange, commodity and bond trading and chose not to enter the stock market for the time being, because their diversity is high and the value of each stock is highly dependent on the unique circumstances of the companies.

Jim Simons dreams of a trading system that is completely driven by algorithms without the intervention of human judgment; But the computers of the eighties did not have the ability to run fully automatic programs. For this reason, the Renaissance initially used both mathematical models and human judgment, which became troublesome for him; For example, Baum bought tens of millions of dollars in bonds in 1984, but held them until they fell in value and put the company under heavy pressure; Until Simons went as far as giving up on the renaissance.

Simons and Ax launched a new hedge fund called Medallion, named after the prestigious math awards they won. The medallion fund initially had many problems, but eventually became the most successful hedge fund in history. After ten years of improving algorithms and progressing the processing power of computers, the turning point of the renaissance came in 1990.

Edward Trapp , the first modern mathematician who made a huge investment fortune using the Cammy Simons strategy, wrote in the Wall Street Journal article, “Computer Formulas Are the Secret to Market Success”:

A computer model is a simplified version of reality, like a street map that shows how to travel from one point of a city to another. If you design them right, you can use its rules to predict what will happen in new situations.

Renaissance models were so successful in trading that Siemens continued to trust its computers even in decisions that didn’t seem logical. The only problem was that Renaissance was very small, and after ten years its assets were only a quarter of those of rival DE Shaw; David Shaw not only used computer models for trading, but unlike the Renaissance, he also went to the stock market.

Simons knew that in order to leave a legacy, he had to enter the stock market; That’s why he hired Robert Mercer and Peter Brown , who had become famous for the great speech-to-text achievement at IBM. The two looked at language as a game of possibilities in which some words followed other words. Siemens wanted a similar system that could predict financial market trends. Brown and Mercer designed an automated stock trading system in 1995 that was written in half a million lines of code, compared to the tens of thousands of lines of code in the old system.

With Renaissance entering the stock market, the medallion fund soared. In 2000, Medallion returned an astonishing 98.5% including losses, during the dot-com bubble, during which many telecommunications companies went bankrupt and larger companies such as Amazon and Cisco lost much of their market value. They gave.

The Medallion fund made more than $100 billion in profits between 1988 and 2018, and as of summer 2019, its annual return before deficits was about 66% and after deficits was about 39%. In 1993, the fund was closed to new investors, and since 2005, only Renaissance employees are allowed to invest in it. With their windfall, these employees bought so many mansions in the Old Field neighborhood of Long Island that the neighborhood was nicknamed the “Renaissance Riviera.”

Medallion’s astonishing performance made Simons the 50th richest person in the world at the time of his death, with a fortune of $31.4 billion. Simmons first appeared on Forbes magazine’s list of the richest Americans in 2004 with a net worth of $2.5 billion.

Currently, Renaissance is led by Peter Brown and has about 300 employees consisting of 90 scientists with PhDs in mathematics, physics, computer science and related fields. The research database of this company hosts more than 40 terabytes of data daily and uses 50,000 computer cores with a global connection of 150 gigabytes per second.

Quantitative strategies, based on more conservative models, have become popular on Wall Street since Simons revolutionized the trading world in the 1980s, and the funds now account for little more than 20 percent of all equity holdings.

But how Renaissance was able to achieve such startling results remains among the company’s top secrets, and employees are not allowed to talk about Renaissance’s algorithms. Simmons also had a very secretive personality and rarely appeared in public. Although he never talked about the Renaissance Algorithm, he did share the secret of his success; That “he never turned his back on the model.” Once Simons had decided what to do, he stood his ground until what the model predicted happened.

The success of the Renaissance is also a reminder of the predictability of human behavior. Renaissance studies the past because it is certain that investors will make similar decisions in the future. At the same time, company employees avoid emotional and emotional biases by relying on the scientific method. They hypothesize, then test and measure, and rely on data instead of instinct when making decisions.

In 2009, Simons decided to step down from the management of Renaissance and hand over the leadership of the company to Robert Mercer and Peter Bervan. Having amassed an impressive fortune over two decades, Simons decided to spend a large portion of it on philanthropic causes.

According to estimates, Simons spent more than $6 billion of his fortune on philanthropic causes and was ranked the sixth most philanthropic person in America by Forbes magazine. Jim credited Marilyn as the driving force behind the Simons Foundation, joking, “I just make money and Marilyn gives it all to charity.”

Speaking at MIT in 2010, Simons outlined the five pillars that have shaped his life and career in mathematics, investing, and philanthropy: “Do something new; Don’t go with the crowd; Surround yourself with the smartest people you can find; Go for beauty; Don’t give up easily and wish for luck!”