NEW YORK (Reuters Breakingviews) - It’s a challenge for the subject of a 359-page biography to remain a cipher. But Jim Simons has always been up for a test. The mathematician and founder of Renaissance Technologies, the super-secretive quantitative investment firm, created the flagship Medallion fund in 1988. It has since produced average returns of a mind-boggling 66% a year, before fees. All this from a man who never took a finance class. But the most interesting subjects in “The Man Who Solved the Market” are the models Simons helped design, and the math behind them.
The octogenarian apparently isn’t thrilled to be the subject of Gregory Zuckerman’s book. This could be because John Paulson suffered poor returns after the author made the hedge fund manager the star of a previous book, “The Greatest Trade Ever”. The real reason is more likely Simons’ secrecy. He’s a prize-winning mathematician who helped crack Cold War codes and led a university department before becoming one of the most successful investors of all time. His net worth was rumored to be around $23 billion in 2018. But most people have never heard of him.
That is clearly by design. Simons views the market as a code to be cracked, and no codebreaker wants to signal his presence. This focus explains Renaissance’s hiring practices. It mostly favors mathematicians over traders or economists and makes employees sign super-strict non-disclosure agreements. It also explains Simons’ focus on collecting and scrubbing enormous amounts of data in the search for statistically significant patterns.
This is where the book gets interesting. Simons views gyrations in financial markets as a hidden Markov model: a sequence of seemingly random events that are actually governed by concealed variables. He believes that markets exist in different states, and that short-term relative movements in asset prices can be better predicted by using algorithms that infer this hidden structure. While he originally incorporated some gut instinct into his trading, he eventually gave up most control to the algorithms.
Importantly, a model built using this concept isn’t designed for perfection. Instead, it’s designed to make better predictions. Understanding the difference between the probability of success and the guarantee of success appears to have helped Renaissance survive the fate of rivals like Long-Term Capital Management, which failed after Russia devalued the ruble in 1998.
The description of how the Medallion trading system functions is downright beautiful, even for readers who aren’t math geeks. It designs a multitude of trades that work in concert to generate high returns at low risk across asset classes, in such a way that patterns normally remain hidden to other traders. This mathematical ballet produces shockingly high Sharpe ratios – a common measure of risk-adjusted returns. In early 2003 the Medallion fund achieved a ratio of six, nearly twice what the biggest quant funds would hope for.
Medallion had some help, particularly from the use of basket options. These are derivatives whose value is tied to a basket of underlying securities. Banks like Deutsche Bank and Barclays held and traded the actual securities according to instructions from Renaissance computers. This enabled the firm to wager far more capital than it controlled, seriously boosting returns. But unlike more conventional leverage strategies, such as those used by LTCM, the risk remained mostly with the banks. The most Renaissance could lose was the option premium and its collateral.
This strategy also may have helped Medallion investors avoid paying short-term capital gains taxes. The U.S. Internal Revenue Service rejected an appeal involving another firm’s use of these tools. This doesn’t bode well for Renaissance, which is in a similar dispute over around $6.8 billion in unpaid taxes, according to a U.S. Senate investigation. The IRS changed the accounting treatment of these options in 2015.
“The Man Who Solved the Market” is well researched and easily digestible, which is somewhat surprising for a book that includes descriptions of differential equations and geometrical concepts such as holonomy. But it also has some distracting quirks. Zuckerman includes novelistic details, like Simons looking out of a window on a particular day, that are obviously imagined. He also ends chapters with gimmicky cliff-hanger sentences.
Toward the end, the book’s focus shifts to Robert Mercer, who became the co-chief executive of Renaissance with Peter Brown in 2010 before standing down in 2017. It’s interesting that Mercer, a noted conspiracy theorist and supporter of President Donald Trump, also backed a congressional candidate who collected vials of human urine in the belief it could help him live forever. But it’s a testament to the appeal of Zuckerman’s algorithmic subjects that readers will find themselves saying: enough with these weird, unlikable, humans. Let’s get back to the math.
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