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The world's smartest billionaire

James Harris Simons, Chairman, Renaissance Technologies


He is known as the "Quant King" in the world of global hedge funds, and a pioneer of what we now know as quantitative research or quant based investing. His net worth is estimated at US$ 16.5 billion, which gives him the 50th position in the Forbes list of richest people in the world. In 2006, Financial Times named him the "world's smartest billionaire". He started his career as a code breaker with the US Government's National Security Agency. He built his fortune by applying his mathematical genius of understanding patterns in data, to the world of investments, and in the process helped create a whole new investing style called quant investing.

James Harris Simons is that type of person who, by nature, changes the way the world works. He was the first to introduce quantitative techniques to predict stock price movements, in the process, becoming one the richest men in the world.

When one looks for an investment manager, a career as a mathematician, who once worked for the US government's National Security Agency breaking secret codes, is hardly the background that one would want to see. Yet Simons is all that and what is more, even now after all these years, he remains steadfast in his love for math.

Early life

Born in 1938, Simons quickly discovered his lifelong love for mathematics. Yet, at age 14, he was dismissed from a stock boy's job; for poor memory! However, working purposefully, Simons got admission in MIT and majored in mathematics. He moved to the University of California, Berkeley for his PhD. which he obtained at just 23 years of age. His first job was as a code breaker at the National Security Agency. As the love for math still burned in his heart, he left the NSA job after four years and took up a position as a math professor at Stony Brook University.

Turning to Trading

It was only in 1978, when he started managing his father's money, that he started showing any interest in finance. This experience led him to start his hedge fund Monemetrics. As he gained experience and confidence, he realised that statistical and mathematical models to analyse the data could be profitably applied to stock trading. By 1988, Simmons was using such models alone for deciding the trades he made. He hired physicists, data analysts and mathematicians to work in his fund. The company prospered using the techniques developed by this group.

Investment philosophy

Simons began by looking at patterns of prices. When he began investing, he says that he was like other investment managers. Initially he was very successful. Yet success proved to be a fickle mistress. "You know you come in one morning, you think you're a genius. The markets are for you. We were trading currencies and commodities and financial instruments and so on, not stocks, but those kinds of things. And the next morning you come in, you feel like a jerk. The markets are against you. It was very gut-wrenching," he says. (David Foulke, Alpha architect, June 3, 2015)

So he started to look at the patterns of stock prices. His mathematical brain grasped that price variations were statistically predictable. He started to build mathematical models to predict stock price behaviour. He and his team worked ceaselessly on these models to make them as perfect as possible, allowing Simons to dispense with fundamental methods of studying stock price movements.

The second pillar of his philosophy is the study of costs of trading. When individuals buy or sell a few hundred shares on the market it will not alter prices. But when investment houses buy two or three hundred thousand shares that is bound to cause a change in stock prices. "You have to know what you're costs are when you trade. You're going to move the market when you trade. How much are you going to push the price? How are you going to, you know, are you going to push it so far that you can't make any money because you've distorted things so much? So you have to understand costs, and that's something that's important. And then you have to understand how to minimize the volatility of the whole, of the whole assembly of positions that you have, and be, so you have to do that. That last part takes some fairly sophisticated applied mathematics, not earth-shattering, but fairly sophisticated."

On the kind of stocks he trades. "We have three criteria: If it's publicly traded, liquid and amenable to modelling, we trade it. Stocks are chosen based on signals generated by a series of proprietary predictive systems." (

Investment strategy

Simons is secretive when it comes to his investment strategy. "Of course we can't show the model or tell people how we calculate our forecasts. That would be like Warren Buffett telling the world what stocks he's buying before he buys them."

However it is possible to glean some details from his actions and interviews. "It's mostly statistics. It's mostly statistics and some probability theory. And, but, I can't get into what things we do use, and what things we don't use."

He does not believe in the 'efficient market' theory which means that the price of a stock at a certain point of time is always the correct one. "But that's just not true. So there are anomalies in the data. Even in the price history data. But gradually we found more and more and more and more anomalies. None of them is so overwhelming that you're going to clean up on a particular anomaly. Because if they were, other people would have seen them, so they have to be subtle things. And you put together a collection of these subtle anomalies and you begin to get something that will predict pretty well." (David Foulke, Alpha architect, June 3, 2015)

"Weather, annual reports, quarterly reports, historic data itself, volumes, you name it. Whatever there is," he says. "We take in terabytes of data a day. And store it away and massage it and get it ready for analysis. You're looking for anomalies. You're looking for - like you said, the efficient market hypothesis is not correct."

Simons believes in making models as accurate as possible. "We reach for different things that come, that might be effective. So we're very universal, we don't have any, but it's a big computer model. For one thing there is a capacity to the major model. It can manage a certain amount of money, which is rather large. But it can't manage an enormous amount of money because you're pushing, you're going to end up pushing the market around too much, so it was kind of a sweet spot as to how much it's reasonable to manage."

"You can see an anomaly that's persistent for a sufficiently long time - the probability of it being random is not high," he said. "But these things fade after a while; anomalies can get washed out. So you have to keep on top of the business."

On the best time he would choose to invest. "Those kinds of times… when everyone is running around like a chicken with its head cut off, that's pretty good for us…" (


The extraordinary success of his company Renaissance Technologies can be attributed to Simons's ability to hire the right people as much as to his passion for math. The reason for Renaissance's success is machine learning and improving the different predictive techniques over time.

"I did it by assembling a wonderful group of people. We just hired smart people. My algorithm has always been, you get smart people together. You give them a lot of freedom. Create an atmosphere where everyone talks to everyone else. They're not hiding in a corner with their own little thing. They talk to everybody else. And you provide the best infrastructure, the best computers and so on that people can work with. And make everyone partners. So that was the model that we used in Renaissance. So we would bring in smart folks and they didn't know anything about finance, but they learned." (David Foulke, Alpha architect, June 3, 2015)

Again, "mathematics and science are two different notions, two different disciplines. By its nature, good mathematics is quite intuitive. Experimental science doesn't really work that way. Intuition is important. Making guesses is important. Thinking about the right experiments is important. But it's a little more broad and a little less deep. So the mathematics we use here can be sophisticated. But that's not really the point. We don't use very, very deep stuff. Certain of our statistical approaches can be very sophisticated. I'm not suggesting it's simple. I want a guy who knows enough math so that he can use those tools effectively but has a curiosity about how things work and enough imagination and tenacity to dope it out." (

Thanks to his phenomenal investing prowess, James Simons' net worth is currently estimated at US$ 16.5 billion. He retired from active fund management in 2009, but continues to be the chairman of the company he founded, and spends most of his time currently in philantrophy. In the mundane world of international finance and stock markets, mathematics, statistics and probability theory make for an exotic cocktail. Yet this is precisely what James Harris Simons, known as the 'Quant-king' has put together for his remarkable success in the stock markets.


Content is prepared by Wealth Forum and should not be construed as an opinion of HDFC Mutual Fund.

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