THE MAN WHO SOLVED THE MARKET: HOW JIM SIMONS LAUNCHED THE QUANT REVOLUTION BY GREGORY ZUCKERMAN

BOOK REVIEWS BY BINOD

BINOD’S RATING: 7/10

Jim Simons started a radical investing approach by crunching data and creating predictive algorithms—years before these tactics became popular. Today, quant investors are the market’s largest players, controlling 31% of all stock trading, inspired by the success of Simons and his colleagues. 

Simons is the greatest money maker in modern financial history. No other investor--Warren Buffett, Peter Lynch, Ray Dalio, Steve Cohen, or George Soros--can touch his record. Since 1988, Renaissance's Medallion fund has generated average annual returns of 66%. The firm has earned profits of more than $100 billion; Simons is worth $23 bln. 

Working with a handpicked team of brilliant mathematicians, Simons pioneered a data-driven, algorithmic approach. For this approach to work, the team needed even more data than they had collected. So they began to model data; to deal with gaps in the historical data, they used computer models to make educated guesses as to what was missing. The model began by making predictions for various commodity prices based on complex patterns, clusters, and correlations that no one understood or detect with the naked eye. It was a black box approach that was perplexing yet delivered results. Simons & co eventually had to accept that machines were capable of something humans could neither do nor understand! 

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Yet, Simons never placed too much trust in the models. Yes, the firm’s system seemed to work, but all formulas are fallible. This conclusion reinforced the fund’s approach to managing risk. If a strategy wasn’t working, or when market volatility surged, Renaissance’s system tended to automatically reduce positions and risk. 

The book does refer to hidden Markov models, kernel methods of machine learning, and stochastic differential equations but overall it’s very readable and almost unputdownable, like a thriller. 

For students of finance, it’s a peek into the new world where machines play an even bigger role in making money. It’s important to grasp what works (and doesn’t work) and why and it’s essential learning.