“Higher mathematics may be dangerous and lead you down pathways that are better left untrod.”
— Warren Buffett, 2009 Berkshire Hathaway Annual Meeting
Success in most areas of life requires having a clear and coherent view of reality along with the mental fortitude to pursue your goals consistently over a long period of time. From an economic standpoint, doing things that are easy to implement and obvious to everyone else is unlikely to yield more than middling results. Whether you are opening a new restaurant, writing a book, or trying to achieve superior results in financial markets, you need to establish an edge of some kind if you hope to enjoy above average results. The world is simply too competitive to bestow great success on people who never stray from doing what everyone else is doing.
It is important to recognize that there is no single path to success in most fields because every human being is born with unique attributes and develops further strengths and weaknesses over time based on the environment in which they live. Innate intelligence and talent combined with the circumstances of the first two decades of our lives plays a huge role in how we see the world and the manner in which we go about trying to achieve our goals. New skills and talents can certainly be developed, but underlying temperament and interests drive and define us from a relatively early age. Someone who is obsessed with business and making money from an early age is likely to approach investing with a different perspective than an equally intelligent person who had an early obsession with mathematics and science.
In 1959, Jim Simons was a twenty-one year old newly married graduate student at the University of California, Berkeley with a $5,000 wedding gift1 that he was eager to turn into a greater fortune. After an initial foray into stocks that barely moved and bored Simons, his broker suggested buying soybean futures. Simons quickly earned thousands of dollars in profit, only to lose the gains within a few days. This experience was enough to hook the young mathematician who became fascinated with financial markets and the possibility of scoring short-term profits. Simons, who is now a 81 year-old multi-billionaire, went on to achieve goals beyond his wildest expectations from that modest start sixty years ago. Although Simons was not eager to have his story told, Gregory Zuckerman managed to uncover many fascinating details regarding Simons and the firm he founded. The Man Who Solved The Market is a riveting account of how Simons used his mastery of mathematics to achieve enormous success in financial markets.
“It’s nice to be very rich”
Jim Simons had no interest in business during his formative years, but he did have an interest in money. He grew up in a family of fairly modest means, but was exposed to wealth at an early age and observed that “it’s nice to be very rich”. However, his natural inclination was to pursue science and mathematics rather than business. Like Warren Buffett, Simons had very unusual skills with numbers as a young boy but, unlike Buffett, Simons was attracted to the elegance and beauty of pure mathematics and intellectual life. The problem with the intellectual life of an academic is that it can lack adventure, and Simons soon had an “existential crisis” at the age of twenty-three wondering whether he would be stuck in an academic rut for the rest of his life.
Simons had a meteoric early rise in academia and accepted a position at Harvard in 1963 where he established himself as a popular professor, but he was not satisfied with the pay and taught additional courses on the side at a community college. Simons “hungered for true wealth” and saw how money can buy influence and independence. He soon left Harvard to join the Institute for Defense Analysis (IDA) where he doubled his academic salary and, perhaps more importantly, began his lifelong quest to come up with a system to profit in financial markets.
Simons was a code breaker at IDA focused on cracking Russian codes and ciphers that had been impenetrable for over a decade. Simons would spend his days creating algorithms based on mathematical models designed to interpret patterns in the data. Simons did not have expertise in programming but proved to be a master at developing algorithms that others would encode. He achieved a breakthrough that leveraged an error in the Soviet code to gain insight into the construction of the system and developed the means of exploiting it.
Why Ask Why?
Inspired by his success in code-breaking, Simons used the flexibility he enjoyed at IDA to develop a unique stock trading system on the side, along with his colleague Lenny Baum:
Here’s what was really unique: The paper didn’t try to identify or predict these states using economic theory or other conventional methods, nor did the researchers seek to address why the market entered certain states. Simons and his colleagues used mathematics to determine the set of states best fitting the observed pricing data; their model then made its bets accordingly. The why’s didn’t matter, Simons and his colleagues seemed to suggest, just the strategies to take advantage of the inferred states.
The Man Who Solved The Market, p. 29
Simons approached financial markets in a manner diametrically opposed to the fundamental analysis practiced by investors such as Warren Buffett. Simons did not care about the underlying economics of the financial instruments he sought to trade. He did not scrutinize macroeconomic variables such as GDP growth, inflation, housing starts, or rail shipments, nor did he analyze microeconomic variables specific to individual businesses. Simons focused exclusively on what he could learn by observing market data and detecting hidden patterns in that data that could be exploited for short term gain. It would have been just as impossible for Simons to adopt Buffett’s approach as it would have been for Buffett to adopt Simons’s approach. Simons had no interest in business and Buffett had no interest in attempting to understand the minute-by-minute gyrations of financial markets. Each brought to the game their own personal proclivities and talents.
Simons returned to academia when an opportunity came up to lead the mathematics department at SUNY Stony Brook on Long Island. His work on predicting financial markets was still fairly crude and he did not implement it for several years but the seed had been planted in his mind. By 1978, Simons decided to leave academia for good and founded what would eventually become Renaissance Technologies.
A Pure System
“I don’t want to have to worry about the market every minute. I want models that will make money while I sleep. A pure system without humans interfering.”
Jim Simons quoted in The Man Who Solved the Market, p. 56
Readers of Zuckerman’s book will never get a true sense of how the systems Simons and his colleagues built actually work. For one thing, the mathematics behind the systems are no doubt penetrable only to experts. These are models developed over decades by dozens of PhDs who worked with Simons to perfect his trading models. In addition, the models are obviously proprietary and Zuckerman’s sources were mostly bound by nondisclosure agreements. So readers looking for magic formulas will be disappointed but those of us looking for a fascinating story will enjoy the details nonetheless.
The early efforts of Simons, Lenny Baum, and James Ax led to success in developing models for various commodity, bond, and currency markets with positions generally held for a day or less. The system provided encouraging early results but it took on a life of its own and made strange decisions that no human could discern, leading to odd situations like nearly cornering the global market for potatoes. In the early 1980s, Baum shifted to a more traditional fundamental style of investing and Simons branched out into venture capital. Baum in particular began to take positions using intuition and instinct and started to make significant money for the firm.
A pattern seems to emerge in the book where Simons and his colleagues develop systems with a high degree of automation but they never seem to fully trust these systems, often falling back on intuition and instinct which eventually fails. Baum ran into trouble in 1984 with a bet on bonds that was poorly timed and caused a rift with Simons and Baum’s departure from the firm. Years later, James Ax would come to rely on his instincts for a portion of the portfolio he managed, leading to his departure in favor of a more automated system put in place by Elwyn Berlekamp. It seemed like the mathematicians did not fully trust their own models.
Medallion Fund
In 1988, Simons founded the Medallion Fund but he did not experience immediate success and, within six months, the fund was suffering. However, by the end of the year, the fund was up 16.3 percent before fees and 9 percent after fees. Medallion was small initially with assets of just $20 million. Simons was well beneath the radar of Wall Street and Medallion was destined to remain a small player for several years.
Over the next five years, Medallion strung together several years of impressive performance, culminating in an amazing 93.4 percent gross return in 1994. However, Medallion had problems scaling up in size because its trading strategy was limited in terms of the amount of capital it could successfully employ without moving the market. Simons closed the fund to new investors in 1993 when assets reached $280 million due to worries that it was becoming too large.2
Simons realized that he would have to extend Medallion’s portfolio to equities in order to grow the business beyond its traditional focus on commodity, currency, and bond markets. A key turning point came in 1993 when Simons hired Peter Brown and Robert Mercer, both computer scientists recruited from IBM. Mercer and Brown used their coding skills to build a system that would implement a single trading model for all of its investments rather than specific models for different investments and market conditions. Their model was built to handle complications that previous models could not handle or simply ignored.
Even geniuses make mistakes and one amusing part of the story involves a bug in Mercer’s code discovered by David Magerman:
Early one evening, his eyes blurry from staring at his computer screen for hours on end, Magerman spotted something odd: A line of simulation code used for Brown and Mercer’s trading system showed the Standard & Poor’s 500 at an unusually low level. This test code appeared to use a figure from back in 1991 that was roughly half the current number. Mercer had written it as a static figure, rather than as a variable that updated with each move in the market.
The Man Who Solved The Market, p. 194.
Magerman’s insight marked a turning point. Medallion’s equity team started to post better results, but equities were still providing only 10 percent of the firm’s profits in 1998. By 2003, however, Brown and Mercer’s stock trading group’s profits were twice as large as the profits from Medallion’s other trading strategies. Zuckerman goes into some detail regarding how this was accomplished through the use of basket options and substantial leverage. With the equity market puzzle solved, Medallion was able to grow significantly reaching about $5 billion by 2002.
Returning Capital
Medallion’s amazing performance in later years must be understood in the context of the policy of returning capital to investors on an annual basis. The size of the fund remained nearly static from 2002 through 2009 at $5 billion while net returns ranged from 22 to 82 percent over that span. Obviously, retaining these gains and reinvesting in Medallion’s strategy was not possible. If it had been possible, the size of Medallion would have grown exponentially. Instead, capital had to be returned to investors who, by this point, were mostly comprised of current and former Renaissance employees.
In an appendix to the book, Zuckerman presents a chart comparing the returns of Medallion with the records of George Soros, Steven Cohen, Peter Lynch, Warren Buffett, and Ray Dalio. Simons trounces all of these men in the table Zuckerman presents. However, there are problems with this direct comparison. For one thing, the period during which the returns were generated vary greatly with some investors having much longer track records than others. More importantly, Warren Buffett’s Berkshire Hathaway posted the 20.5 percent annualized returns from 1965 to 2018 while retaining all of the capital generated over the decades.3 Additionally, Zuckerman does not include Simons’s record prior to Medallion fund, which was not as impressive, while excluding Buffett’s early record which was even more impressive than his record at Berkshire.
Many Ways to Win
Intellectual humility requires us to recognize that there are many ways to succeed in any given field. For a value investor, the manner in which Jim Simons generated his wealth might seem like casino gambling and, indeed, it does share some characteristics with the economics of the “house” in a casino. By developing models that predict human behavior, Simons can be right just slightly more than half the time and still grow fabulously wealthy. He used his innate talents and interests to “solve the market” in his own way.
A value investor like Warren Buffett, on the other hand, takes exactly the opposite approach and scrutinizes businesses looking for enduring competitive advantages and then holds those investments for years or decades. Buffett’s temperament lends itself to this style of investing and it is arguable that Buffett’s approach is far more comprehensible for the vast majority of investors. Most of us are not math geniuses like Simons. Most of us are also not business geniuses like Buffett. But we can at least comprehend Buffett’s strategies and the manner in which he built his wealth is more accessible because he did so in the form of a public company. We can also invest alongside Buffett whereas we cannot invest with Simons given restricted access to his investment vehicles.
Ultimately, we all need to decide how we will approach investing. First, we have to decide whether to try to beat the market at all. Once we decide to make that attempt, we need to figure out what our edge is. Can we compete with men like Jim Simons at his game? The prospect of doing so seems very unlikely. But we can compete with Warren Buffett, especially since Buffett can no longer play in smaller opportunities given Berkshire’s massive size. And if we do not want to compete with Buffett, we can at least invest along with him, and we can do so in an investment vehicle that carries minimal fees and, thus far, has been able to reinvest all of its capital.
Disclosure: Individuals associated with The Rational Walk LLC own shares of Berkshire Hathaway.
- $5,000 in 1959 dollars is nearly $44,000 in 2019 dollars due to the effects of inflation. Simons was playing with a substantial sum of money for a young, newly married graduate student. When reading about dollar amounts in the 1950s, one can simply add a zero to the figure to approximate the ravages of inflation over six decades. [↩]
- Zuckerman provides detailed performance data for Medallion in Appendix 1 to the book. The net performance is even more remarkable in light of the extremely high fees. Medallion has always carried a 5 percent management fee. The performance fee was initially 20 percent but was later raised to an astounding 44 percent! Despite the burden of these fees, Medallion had 39.1 percent average returns from its founding in 1988 through the end of 2018. [↩]
- With the exception of a single ten cent dividend paid by Berkshire Hathaway in 1967 [↩]