Notes - The Man Who Solved the Market

October 19, 2024

Chapter One: Money Isn’t Everything

Early Life and Fascination with Math

James "Jimmy" Simons's lifelong preoccupation with mathematics began at a young age. At three, he could double and divide numbers, figuring out all powers of 2 up to 1,024. His early reasoning about a car never running out of gas (always half remaining) demonstrated his unique mathematical perspective. When he was fourteen, working at Breck’s garden supply, he was demoted from stockroom work to sweeping floors because he was too lost in thought to keep track of supplies. This "demotion" felt like a "stroke of luck" as it allowed him to ponder math, girls, and the future. When the store owners laughed at his ambition to study mathematics at MIT, Simons was unfazed, possessing "preternatural confidence" and determination.

Parental and Grandparental Influence

His mother, Marcia, a sharp intellect, "funneled her dreams and passions" into Jimmy, pushing him academically and seeing him as "her project". His father, Matty, who had to work full-time from age six and quit night school due to exhaustion, taught Jimmy the lesson to "Do what you like in life, not what you feel you ‘should’ do". Matty also enjoyed concocting outrageous stories to fool Marcia, a family game that delighted Jimmy. His Russian-native grandfather, Peter, introduced him to "naughty stories" and key Russian phrases, and notably, always carried $1,500 in his breast pocket, even when he died, likely to shield it from taxes.

Education and Early Experiences

Despite a doctor's suggestion to pursue medicine, Simons insisted he wanted to be a mathematician or scientist, even though he didn't fully understand what mathematicians did, and the doctor warned him he couldn't make money in it. In school, he was smart and mischievous, often lost in thought, but captivated by mathematical concepts. He enjoyed visiting the library to take out books "well above his grade level". Observing a wealthy friend's lifestyle, he noted, "It’s nice to be very rich. I observed that," indicating an early interest in money, though not business.

After graduating high school in three years, Simons embarked on a cross-country drive with his friend Jim Harpel. This trip exposed them to severe poverty and racial discrimination in the South, particularly in Mississippi where they saw African Americans working as sharecroppers and living in chicken coops, and were shocked to hear a park employee use a racial slur. These experiences "left a mark on the boys, making them more sensitive to the plight of society’s disadvantaged".

MIT and Mathematical Epiphanies

Simons enrolled at MIT, skipping his first year of math thanks to advanced placement. He struggled initially with a graduate abstract algebra course, but after studying a book on his own, "it clicked," and he aced subsequent classes. Despite a 'D' in an upper-level calculus course, his professor allowed him into the next level where he "blossomed," fascinated by Stokes’ theorem, which unified calculus, algebra, and geometry. He realized he might not be "spectacular or the best" compared to peers like Barry Mazur, but he had a "unique approach," pondering problems for hours to arrive at original solutions, possessing "good taste" for breakthrough problems. An "epiphany" occurred when he saw professors discussing math late at night, deciding he wanted that life of "cigarettes, coffee, and math at all hours".

Outside of math, Simons avoided demanding courses, opting for archery to avoid showering. He was known for mischievous pranks, including creating a homemade flamethrower with lighter fluid and causing a bathroom bonfire in his dorm, for which he had to pay $50 for repairs.

Adventures and First Foray into Business

After graduating MIT at age twenty, Simons sought a "historic" adventure. He and two friends, Joe Rosenshein and Jimmy Mayer, embarked on a scooter trip to South America, "Buenos Aires or Bust," traveling through Mexico, Guatemala, and Costa Rica, overcoming mudslides and rivers. In a small Mexican town, they were surrounded by fifty hostile men with machetes before police intervened.

Upon returning for graduate studies, Simons became engaged to Barbara Bluestein, marrying her in Reno, Nevada, on a budget of borrowed money and poker winnings. As a wedding gift, they received $5,000, which Simons eagerly invested in United Fruit Company and Celanese Corporation, becoming "hooked" on the "action and the possibility I could make money short-term". He ignored advice to sell, and though soybean prices tumbled, he "barely broke even," which only "whet Simons’s appetite". He stopped trading reluctantly when Barbara became pregnant and juggling studies and trading became too much.

Existential Crisis and Academic Transition

Simons completed his PhD thesis, "On the Transitivity of Holonomy Systems," in just two years, dealing with the geometry of multidimensional curved spaces. Despite a prestigious teaching position at MIT, he felt an "existential crisis" at twenty-three, questioning if this was "it" for his whole life. He sought new adventures, returning to Bogotá to start a vinyl floor tile and PVC piping factory with his former schoolmates. Feeling he had little to contribute to the business, he returned to academia, accepting a research position at Harvard in 1963. He taught advanced courses he didn't fully know, learning alongside his students, which they found amusing.

Despite his popularity as a professor, his research was slow, and he didn't enjoy the Harvard community. He had borrowed money for the factory and persuaded his parents to mortgage their home for their share, leading to financial pressure. He secretly taught additional courses at Cambridge Junior College to "pad his income". Simons "hungered for true wealth," understanding that "money is power" and he "didn’t want people to have power over him". His mounting pressures ultimately led him to seek a new path.

Chapter Two: What’s the difference between a PhD in mathematics and a large pizza? A: A large pizza can feed a family of four.

Code-Breaking for the Cold War

In 1964, Simons left Harvard to join the Institute for Defense Analyses (IDA) in Princeton, New Jersey, an elite research organization assisting the National Security Agency (NSA) in detecting and attacking Russian codes and ciphers. The job doubled his salary and allowed him to continue his math research. The IDA taught him to develop mathematical models for discerning patterns in "seemingly meaningless data," using statistical analysis and probability theory. He created algorithms for code-breaking, relying on in-house programmers for the actual coding, honing skills that would be valuable later. He quickly helped develop an "ultrafast code-breaking algorithm" and, with two colleagues, exploited a Soviet coded message glitch, earning them thanks from Defense Department officials. The secrecy of his work meant he couldn't share accomplishments with his wife, Barbara, who eventually stopped asking.

Culture at IDA and Early Business Attempt

Simons was struck by the IDA's unique approach to talent: hiring doctorates for their "brainpower, creativity, and ambition" rather than specific expertise, with the assumption they would solve problems. The credo of top code-breaker Lenny Baum was: "Bad ideas is good, good ideas is terrific, no ideas is terrible". The division was an "idea factory," fostering openness and collegiality among its twenty-five mathematicians and engineers who shared the same title, credit, and celebrated breakthroughs with champagne. Simons and Barbara hosted regular dinner parties with high-stakes poker games, where Simons often won his colleagues' cash. He was once arrested for accumulated parking tickets, and his colleagues chipped in for his bail.

Simons decided to start a company, iStar, to electronically trade and research stocks, believing securities firms were slow to adopt new technology. His boss, Dick Leibler, and the IDA's best programmer agreed to join. The secretive plot was exposed when they left their business plan on a Xerox machine. The venture failed due to lack of funding.

Mathematical Breakthroughs

Simons soon made significant progress in his research on minimal varieties, a subfield of differential geometry. This abstract mathematics aims to discover "universal principles, rules, and truths," often leading to practical applications much later. His collaborations, especially with Frederick Almgren Jr., led him to create his own partial differential equation, the "Simons equation," offering a uniform solution through six dimensions and a counterexample in dimension seven. His 1968 paper, "Minimal Varieties in Riemannian Manifolds," became foundational and continues to be cited, establishing him as a "preeminent geometer". A decade later, Chern-Simons theory (developed with Shiing-Shen Chern in 1974) found applications in physics, including string theory and quantum computing. In 1976, Simons received the Oswald Veblen Prize in Geometry for his work.

Pioneering Quantitative Trading Theory

Even while at IDA, Simons searched for new ways to make money. With Baum and two others, he developed a stock-trading system and co-authored an internal, classified paper, "Probabilistic Models for and Prediction of Stock Market Behavior". This paper proposed ignoring traditional "fundamental economic statistics" like earnings and dividends, and instead searching for "macroscopic variables" to predict short-term market behavior. They posited that the market had "eight underlying 'states'" (e.g., "high variance," "good") that could be mathematically deduced from pricing data, regardless of why the market entered those states. This "crude" paper, which assumed "ideal conditions" with no trading costs despite heavy daily trading, was a "trailblazer". It introduced a third approach beyond economic rationale or simple technical analysis, seeking "signals" from data. Simons was part of a "vanguard," arguing it was not important to understand all market levers, but to find a mathematical system for consistent profits. This foreshadowed factor investing and other quantitative methods.

Vietnam War and Firing

The Vietnam War dramatically changed Simons's situation. Protests at Princeton University brought attention to IDA's presence, despite Simons and his colleagues opposing the war. Simons wrote an opinion piece for the New York Times arguing for better uses of national resources than war. He then told a Newsweek stringer that he would devote all his time to personal math research until the war ended. Although this was a personal goal not formally established, his boss, Dick Leibler, learned of it and fired Simons, saying, "You can’t fire me...I’m a permanent member" to which Leibler replied "Jim, the only difference between a permanent member and temporary member is a temporary member has a contract. You don’t". This abrupt firing, especially with three young children, convinced Simons he needed to gain control over his future. Despite offers from schools and IBM, he found teaching dull and considered selling convertible bonds, which disappointed his mathematician friend Leonard Charlap. Simons confessed his ideal job was to chair a large math department, which Charlap helped him secure at SUNY Stony Brook in 1968.

Chapter Three: Getting fired can be a good thing. You just don’t want to make a habit of it.

A New Beginning in Investing

In early summer 1978, Simons found himself in a dreary storefront office in a strip mall, a world away from academia. At forty, with long, stringy gray hair and a slight paunch, he seemed closer to retirement than a breakthrough in the centuries-old investing world. Despite a previous "completely lucky" profit of $1 million from Charlie Freifeld's sugar partnership, Simons had no special trading talent. Yet, he was "bursting with self-confidence". He believed financial markets, though chaotic, contained "defined patterns," like natural systems, that could be mathematically modeled. He named his new investment company Monemetrics, aiming to use math and "big brains" to analyze financial data and find trends.

The Recruitment of Lenny Baum

Simons's ideal partner was Leonard Baum, co-author of his IDA research paper. Baum, born in Brooklyn to Russian immigrants, became a successful code-breaker at IDA, considered "higher than Jim in what we in management used to call ‘lifeboat order’". With Lloyd Welch, Baum developed the Baum-Welch algorithm in the late 1960s, a "notable advance in machine learning" that paved the way for speech recognition (e.g., Google's search engine) and genomics. Though Baum minimized its importance, it allowed computers to "teach itself states and probabilities". Baum was a homebody, quiet and absentminded, once shaving only half his beard while thinking about math. His classified work grated on his wife, Julia, who felt he didn't receive enough recognition or pay.

Initially skeptical and caring little for investing, Baum agreed to help Simons as a favor. Simons presented him with currency charts like a math problem, and Baum quickly hypothesized structure in steady currency moves, like the Japanese yen. He began working weekly, then full-time, developing an algorithm to buy and sell currencies based on trends. This instilled confidence in Simons, who saw "the possibilities of building models". Simons raised enough money for his new fund, Limroy, named partly after Joseph Conrad's Lord Jim, and set up Monemetrics to test strategies. Baum would share in the firm's 25% profit cut. Simons also persuaded James Ax, his Stony Brook recruit, to join, setting him up with his own trading account.

Challenges with Computerization and Trading Style

Simons then hired Greg Hullender, a nineteen-year-old on the verge of being kicked out of Caltech for running an unauthorized stock options operation. Hullender, despite finding Simons's firm "shady," accepted the offer. Simons explained their goal: to develop algorithms to identify "trends that result from hidden actors influencing the market". Within six months, Hullender's figures showed "disturbing losses" from Simons's bond trading. Simons appeared anxious, even telling Hullender, "Sometimes I look at this and feel I’m just some guy who doesn’t really know what he’s doing," comparing himself to Lord Jim who "failed miserably in a test of courage". Simons then expressed determination to build a "pure system without humans interfering," aiming for automation and money while he slept.

Simons amassed "reams of historic data" from World Bank, commodity exchanges, and other sources, some dating back before WWII. Hullender used a supercomputer at Grumman Aerospace to convert old data formats. Carole Alberghine, Simons's former secretary, manually recorded closing prices from the Wall Street Journal and updated hanging graph paper, an activity that once led to permanent injury. The team tested various momentum strategies and correlations (e.g., gold leading silver). They developed "Piggy Basket," a system using linear algebra for automated trade recommendations (not automated trades) for forty futures contracts. Hullender eventually quit, ashamed he couldn't help more, feeling lonely and out of place after revealing he was gay.

Shift to Traditional Trading and Rift with Baum

With Hullender gone, Simons and Baum drifted to a more traditional, intuitive trading style, investing $30 million. Simons even hired a Parisian to translate an obscure French financial newsletter and installed a "red phone" for urgent news, sending Penny Alberghine (Carole's sister-in-law) scrambling to find him and Baum to execute trades. The office culture was informal, with Simons teasing Alberghine and hosting staff on his yacht.

In 1982, Monemetrics became Renaissance Technologies Corporation, as Simons pursued venture capitalism. He also focused on his son, Paul, born with ectodermal dysplasia, who faced insecurities due to his condition. Baum, meanwhile, was highly successful with intuitive currency trading, earning millions and questioning the need for complex models, saying, "It’s so much easier making millions in the market than finding mathematical proof". He was an optimist, preferring to buy and hold, believing courage was needed to ride out downturns.

A major rift emerged in 1979 over gold futures. Simons sold his position when gold topped $700 in January 1980, locking in millions. Baum, however, couldn't bear to sell, despite gold skyrocketing past $800, convinced the trend would continue. Simons, hearing about people queuing to sell jewelry, became "scared" and ordered Baum to "Sell the fucking gold, Lenny!". Baum ignored him, leading to significant losses and triggering an automatic clause that forced Simons to sell Baum's holdings, ending their partnership. This debacle left "deep scars" on Simons, who halted firm trading, and, racked with self-doubt, contemplated giving up trading. He realized he had to find a "different approach".

Chapter Four: Truth . . . is much too complicated to allow for anything but approximations.

Simons's Frustration and Ax's Character

Simons was miserable with the emotional ups and downs of intuitive trading, telling Charlie Freifeld, "It’s just too hard to do it this way. I have to do it mathematically". He resolved to support James Ax, believing him suited to build a pioneering computer trading system.

James Ax, despite his brilliance and acclaim as a mathematician, was known for his intense anger, including driving his foot through a wall and fistfights. Born in the Bronx, he attended Stuyvesant High School and graduated from Polytechnic Institute of Brooklyn. He suffered from Crohn’s disease from a young age. He earned his math PhD from UC Berkeley in 1961, befriending Simons. As a Cornell professor, he co-developed number theory and, with Simon Kochen, worked on the Ax-Kochen theorem, which won them the Cole Prize in 1967. Ax was fiercely competitive, even wearing a ski mask during poker to hide his "tell". He believed mathematicians did their best work young.

Ax's Personal Struggles and Move to Stony Brook

Ax's personal life was fraught; his divorce was bitter, and he lost custody of his sons, whom he abandoned for over fifteen years, a pattern similar to his own father's disappearance. At Stony Brook, he frequently interrupted meetings, leading Leonard Charlap to ring a bell each time. He even got into a fistfight with an associate professor. Despite this, his reputation attracted Michael Fried, whom Ax later venomously vowed to "ruin your career, fair or foul".

Ax at Simons's Firm

In 1979, Ax joined Simons's strip-mall office. He initially focused on market fundamentals but then developed technical trading models using Simons's collected data. His early research was not original, testing trends based on moving averages, similar to other "trenders". However, his models were crude, and the data was error-riddled.

To improve data, Ax relied on Sandor Straus, a math PhD from Berkeley who joined Simons's firm on a one-year leave from Stony Brook. Straus meticulously collected historic commodity-price data from Dunn & Hargitt, merging it with existing data, and obsessed over gathering tick data (intraday fluctuations) using an Apple II computer, even if it couldn't be used immediately. He "transformed into a data purist, foraging and cleaning data the rest of the world cared little about," even verifying prices against old Wall Street Journals.

Straus's clean data helped Ax improve his trading, putting him in "rare spirits". Simons encouraged their new approach. Henry Laufer, a Stony Brook mathematician, joined part-time, working on reversion strategies (prices tending to revert after initial moves). Simons insisted on teamwork and shared credit, which Ax resisted, leading to Ax refusing to speak to Laufer for six months. Ax's quirky behavior included pushing conspiracy theories (Kennedy assassination) and demanding to be called "Dr. Ax".

Ax's Detachment and Growing Tensions

In 1985, Ax and Straus moved the company to California. Ax's personal life remained turbulent, marked by a move to California for "calm" that didn't materialize, and a later abandonment of his children. In Huntington Beach, Ax became increasingly detached from the office, managing remotely from Malibu and later Pacific Palisades, seeking seclusion. He relied on instinct for part of his portfolio, even getting the New York Times early to make overnight trades. His "infatuation with technology" led to an incident where he tried to dry his underwear in an office microwave, causing it to burst into flames. Simons, still a chain-smoker, struggled with the health-conscious California staff.

Tensions between Simons and Ax escalated over expenses and computer upgrades. By 1989, Medallion was losing money, down nearly 30% due to soybean-futures and competition from other trend followers. Simons's accountant ordered Axcom to halt trading based on longer-term signals, only allowing short-term trades. Ax was "furious," vowing to sue Simons for violating their partnership agreement. Simons was under pressure from disgruntled investors. He felt Ax's strategies were "much too simple". Straus refused to take sides, enraging Ax. Simons considered shutting the firm, leading Straus and his wife to plan for the worst.

Berlekamp's Intervention and Ax's Transformation

In summer 1989, Elwyn Berlekamp, seeing an opportunity for an "intellectual exercise," offered to buy Ax's stake. Ax, facing a legal battle he couldn't win, agreed to sell most of his shares. Ax then underwent a "slow and remarkable transformation," moving to San Diego, writing poetry, and enrolling in screenwriting classes. He reconnected with Simon Kochen, collaborating on academic papers, and, after fifteen years, called his sons, expressing regret and forging close relationships. Ax died of colon cancer in 2006, with the Ax-Kochen theorem engraved on his tombstone.

Chapter Five: I strongly believe, for all babies and a significant number of grownups, curiosity is a bigger motivator than money.

Berlekamp Takes the Reins Amidst Wall Street Greed

Elwyn Berlekamp took charge of the Medallion fund in summer 1989, during a period of intense financial industry growth marked by "greed and self-indulgence". This era saw traders like Michael Milken and Ivan Boesky gain wealth through insider trading, defining a culture of seeking "unfair edge" embodied by Gordon Gekko. Berlekamp, an academic with little interest in market rumors or corporate earnings, was an "anomaly". His physical appearance (balding, bespectacled, with a neat beard and multiple pens in his pocket) and absentmindedness (at one conference, his shirttail was out and wrinkled) stood out. Despite his quirks, his mathematical reputation and confidence in Medallion's potential earned him respect.

Shifting to Short-Term, High-Frequency Trading

Berlekamp's first step was to move the firm closer to his Berkeley home. The new office in the Wells Fargo Building, though initially affected by the Loma Prieta earthquake, quickly set up a satellite receiver for real-time futures prices. Berlekamp focused on implementing short-term trading strategies that Ax had resisted, overcoming concerns about brokerage commissions and "slippage" (cost of pushing prices). He challenged the Wall Street dogma of infrequent trading, arguing that Medallion should aim for "smaller, short-term opportunities—get in and get out". He reasoned that frequent trading magnified gains from small edges (e.g., being right "51 percent of the time"), making each individual trade less critical and reducing overall portfolio risk, much like a gambling casino.

The team scrutinized data, identifying "intriguing oddities," such as prices falling before key economic reports and rising after (though not for all reports like the Labor Department's employment statistics), and day-of-the-week patterns (Monday's price action often following Friday's, Tuesday's seeing reversions). Henry Laufer, now working from Simons's Long Island office, discovered the "twenty-four-hour effect" and "weekend effect". Simons and his researchers "didn’t believe in spending much time proposing and testing their own intuitive trade ideas. They let the data point them to the anomalies signaling opportunity". They theorized that "locals" (floor traders) and brokers trimmed positions ahead of weekends or economic reports to avoid risk, and central banks intervened to slow abrupt currency moves, extending trends.

Ghosts, Data Advantage, and Early Success

The system also spotted "barely perceptible patterns" called "ghosts," which, despite no apparent explanation, reappeared frequently enough to be profitable. A key advantage was their access to "more accurate pricing information than their rivals" due to Straus's years of collecting "tick data" (intraday volume and pricing), which was now usable with more powerful MIPS computers. By late 1989, their rebuilt system, focused on commodity, currency, and bond markets, was set to prosper, with gains from "guppies"—small, frequent profits.

Simons learned that "crooked" Canadian dollar futures traders were exploiting Medallion's orders, immediately eliminating Canadian dollar contracts from their system. For much of 1990, Medallion "could do little wrong," with short-term moves dominating. They had their first "$1 million" day, leading to champagne celebrations that became so frequent Simons limited them to 3% daily returns. Despite external skepticism and being viewed as "flakes," Medallion soared 55.9% in 1990 after fees, a "dramatic improvement".

Simons's Intervention and Berlekamp's Departure

Simons's enthusiasm grew, leading him to call Berlekamp "over and over, almost every day". After Iraq invaded Kuwait, Simons, still charting technical patterns on his own, urged Berlekamp to add gold and oil futures to the system. Berlekamp, committed to the automated model, politely refused, saying, "It would be best to let the model run the show and avoid adjusting algorithms". Simons "couldn’t help reacting to the news," fussing with personal trades despite his push for a human-free system. Berlekamp pushed back, declaring, "The system will determine what we trade". Simons did, however, get Berlekamp to buy some oil call options as "insurance" and scaled back the fund's overall positions during Middle East hostilities.

Simons's increasing requests for expansion, more infrastructure, and contributions from Berlekamp, coupled with his persistent calls and claims that the fund "should be doing" 80% annual returns, wore on Berlekamp. Berlekamp, enjoying teaching more, offered to sell his stake, which Simons immediately bought in December 1990. Berlekamp felt he got a "steal," selling his shares for six times what he paid, never expecting the fund to "go through the roof". He later started his own less successful quant firm, Berkeley Quantitative, reflecting his motivation by "curiosity" rather than "money," unlike Simons.

With Berlekamp, Ax, and Baum all gone, Simons was confident he had a "surefire method to invest in a systematic way," searching for overlooked patterns. However, he "didn’t realize his approach wasn’t as original as he believed" and that other traders had already "crashed and burned" using similar methods, or even had "substantial head starts" on him.

Chapter Seven: What had Jim Simons so excited in late 1990 was a straightforward insight: Historic patterns can form the basis of computer models capable of identifying overlooked and ongoing market trends, allowing one to divine the future from the past.

Historical Roots of Pattern Recognition

Simons's conviction that historic patterns could predict the future was not new, with roots dating back to Babylonian times with barley and date prices. Christopher Kurz in 16th century Nuremberg used astrology and tried to back-test signals to predict spice prices. The 18th century Japanese rice merchant Munehisa Homma, "god of the markets," invented candlestick charting, leading to a "reasonably sophisticated reversion-to-the-mean trading strategy" and the idea to "take losses quickly and let their profits run". In the 1830s, British economists sold price charts, and Charles Dow in the early 20th century developed "modern technical analysis". William D. Gann, guided by "That which has been is that which shall be . . . there is nothing new under the sun," claimed huge trading successes based on cycles and retracements, but his record was unsubstantiated and his methods dubious, leading Andrew Lo to call him a "financial astrologer". Gerald Tsai Jr. in the 1960s used technical analysis to manage Fidelity Magellan, but his strategies were "ridiculed" after the 1969-70 bear market. Technical traders eventually became "targets of derision," though some top traders still consult charts. Professor Lo views them as "forerunners" of quantitative investing, but their methods lacked rigorous testing.

Simons, like his predecessors, practiced pattern analysis, but aimed for a "more scientific manner" using rigorous testing and "sophisticated predictive models" based on statistical analysis rather than "eyeballing price charts".

Early Computerized Trading and Quants

The computer age quickly saw investors using machines to solve markets. Barron's magazine (1965) and the Wall Street Journal gushed about computer potential, while author George Goodman (Adam Smith) mocked "computer people". Richard Dennis, the "Prince of the Pit," codified his trend-following rules and taught them to "turtles," staking them with cash. Some "turtles" saw success, and Dennis himself made $80 million in 1986, but he was "crushed" in the 1987 market turbulence, losing half his cash.

Throughout the 1980s, mathematicians and ex-physicists were recruited to Wall Street for "financial engineering" tasks like valuing derivatives and analyzing risk. They were initially called "rocket scientists," then "quants," a pejorative term used by senior managers who prided themselves on "ignorance of computers". Skepticism was warranted: portfolio insurance, a computer-driven hedging technique, was blamed for the 1987 crash. Floyd Norris called it "the beginning of the destruction of markets by dumb computers". Benoit Mandelbrot's fractal theory suggested markets would deliver more unexpected events, reinforcing doubts about elaborate models.

Edward Thorp, a mathematician influenced by Claude Shannon and John Kelly, became the "first modern mathematician to use quantitative strategies to invest sizable sums of money". After successfully beating blackjack and writing Beat the Dealer, Thorp turned to Wall Street in 1964. He developed a formula for pricing stock warrants, using a Hewlett-Packard 9830 computer to find mispricings. His hedge fund, Princeton/Newport Partners, recorded strong gains, attracting investors like Paul Newman. Thorp's formula was influenced by French mathematician Louis Bachelier's 1900 thesis on option pricing. In 1974, the Wall Street Journal featured him. By the late 1980s, Thorp's fund managed nearly $300 million, dwarfing Simons's $25 million Medallion fund. However, Princeton/Newport was "ensnared" in the Michael Milken trading scandal, leading to its closure in 1988, which Thorp described as "traumatic".

Other Quant Pioneers

Gerry Bamberger at Morgan Stanley developed software for "pairs trades," betting on the return of price-spreads to historic levels. By 1985, he was managing $30 million for Morgan Stanley. Nunzio Tartaglia renamed his group Automated Proprietary Trading (APT), adding automation and by 1987 it generated $50 million in annual profits. Their strategy was "simply to wager on the re-emergence of historic relationships between shares".

Robert Frey, a former Morgan Stanley quant, proposed "factor investing," deconstructing stock movements into independent variables (e.g., oil prices, overall market momentum). He applied this to statistical arbitrage, buying undervalued stocks and shorting overvalued ones based on historical factor relationships. His fund, Kepler Financial Management (later Nova), aimed for market-neutral returns with a high Sharpe ratio. However, Kepler's "middling results" frustrated clients, as its profits often "paled in comparison to those predicted by their model". Frey was like a "chef with a delicious recipe who cooked a series of memorable meals but dropped most of them on the way to the dinner table". Renaissance staffers felt his model was too sensitive to market noise.

David Shaw, a supercomputing expert, launched D. E. Shaw, hiring math and science PhDs from diverse backgrounds ("English and philosophy majors," a "chess master," "stand-up comedians") who had "no preconceived notions". His offices were "quiet and somber," resembling a research room. Shaw foresaw the internet's possibilities, even working with Jeffrey Bezos, who later founded Amazon.com. Shaw's fund quickly "minted money," managing hundreds of millions. Simons realized he needed help to catch up to pioneers like Shaw.

Chapter Eight: Jim Simons’s pulse quickened as he approached Sixth Avenue.

Seeking Investment and Confronting Skepticism

In 1991, Jim Simons sought investment from Donald Sussman, a financier backing David Shaw's D. E. Shaw. Sussman believed mathematicians might eventually rival traditional firms. At the time, Simons's Medallion fund managed barely $45 million, a quarter of Shaw's firm. Wall Street mostly "scoffed" at Simons's "black box investing," deeming it "ludicrous, even dangerous". Sussman, recognizing Simons's academic demeanor, was impressed by his pitch, but declined to invest due to conflicts of interest with Shaw and Shaw's superior returns (40% vs. Simons's unstated). Other firms, like Commodities Corporation, also passed on Renaissance, viewing it as "a bunch of mathematicians using computers" with "no track record".

Laufer's Monolithic Model and Machine Learning

Henry Laufer, Simons's "best partner yet," made a "extraordinarily valuable" early decision: Medallion would employ a "single trading model" across various asset classes, rather than separate models. This allowed the model to draw on Straus's vast pricing data, detecting correlations and opportunities that narrow, individual models would miss. It also made it easier to add new investments. Laufer worked to "smooth" wrinkles in combining different investments. Simons then challenged them to dissect intraday pricing information into "five-minute bars" to "unearth new, undetected patterns". Straus's improved computer-processing power made this possible.

Simons then tasked Laufer with developing a "betting algorithm" to identify optimal trades and manage position sizing, dynamically adapting and relying on real-time analysis—an "early form of machine learning". Simons was excited, calling the system "a living thing; it’s always modifying".

New Hires and Initial Skepticism

Simons expanded his staff, including Kresimir Penavic, a PhD student, whom Simons initially "sniffed" at as "trivial stuff" but eventually hired. Nick Patterson, another recruit, was initially suspicious that Simons was running "some kind of scam". Medallion's high returns and Simons's claims seemed too good to be true. Patterson, knowing "Mathematicians can be crooks, too," surreptitiously checked Medallion's reported closing prices against the Wall Street Journal for a month, only dedicating himself to the work after the numbers checked out.

Patterson's background included overcoming facial dysplasia and bullying by becoming the "school brain," using math for "protection". He saw the world becoming "extremely mathematical" and believed Simons had an opportunity to revolutionize investing. Laufer and Patterson developed "sophisticated approaches to direct trades to various futures exchanges to reduce the market impact of each trade," which became a "huge advantage" for the fund. Trading frequency increased from five to sixteen times a day.

Understanding Market Inefficiencies and Behavioral Biases

Simons's team didn't focus on why their algorithms predicted prices. Simons famously said, "I don’t know why planets orbit the sun... That doesn’t mean I can’t predict them". They concluded that their profits came from "exploiting the foibles and faults of fellow speculators," like "a lot of dentists," rather than infrequent "buy-and-hold individual investors". This contradicted academic theories of efficient markets and rational decision-making. Simons's instincts were validated by emerging behavioral economics from Amos Tversky, Daniel Kahneman, and Richard Thaler, who demonstrated how individuals are prone to irrationality (e.g., loss aversion, anchoring, endowment effect). Medallion made its largest profits during "extreme turbulence". Simons committed to not overriding the model, believing human emotions caused market patterns. Researcher Kresimir Penavic explained, "Humans are most predictable in times of high stress—they act instinctively and panic. Our entire premise was that human actors will react the way humans did in the past . . . we learned to take advantage".

Secrecy and Growth Limits

Medallion's success attracted GAM Holding. By the end of 1993, Medallion managed $280 million, and Simons, fearing growth would hurt profits, decided not to accept new clients. The firm increased its secrecy, with a recorded message for results and directing clients to lawyers for updates, to prevent rivals from learning their tactics. Simons pressed investors for a "low profile". This secrecy made recruitment difficult; Michael Botlo, a scientist from Brookhaven National Laboratory, was unimpressed by the bland office, old programming language (Perl, though it was for bookkeeping, not trading), and lack of information, perceiving Renaissance as "four guys in a garage".

Medallion continued its winning streak, but Laufer's models showed returns would wane beyond $600 million. Simons was frustrated by these "capital constraints" and the idea of "signals . . . leaking". Some staffers, like Sandor Straus, wanted to keep the fund at $600 million for consistent wealth. But Simons, driven by a desire to "matter" and "be the best," insisted on growing the fund and becoming a "billionaire". The only way was to expand into stock investing, which had confounded them. This led Simons to consolidate operations on Long Island, causing Sandor Straus to protest and leave.

Personal Tragedy and Firm's Challenges

Simons's old math friends still viewed his focus on finance as a "waste of time" and "frivolity". Dennis Sullivan, a topologist, was "disappointed in his choices" but later softened his view seeing Simons's devotion to his aging parents and children, especially Paul, who suffered from ectodermal dysplasia and later epilepsy. Paul's sudden death in 1996 was a "crushing blow". Simons struggled with intense grief, finding refuge in math. He refocused on the struggling stock-trading efforts, his "last chance to build his firm into a power".

Chapter Nine: No one ever made a decision because of a number. They need a story.

The Challenge of Stock Trading and Fundamental Rivals

Jim Simons knew that for Renaissance Technologies to be significant, its computers needed to make money in stocks. This was challenging in the early 1990s, the "golden age for fundamental investors" like Warren Buffett and Peter Lynch, who relied on "instinct, cunning, and experience". Peter Lynch, managing Fidelity's Magellan fund to 29% annual gains, advocated "Know what you own," researching companies through phone calls and visits, giving him a legal "information advantage". Fidelity analysts would even talk to cabdrivers to gauge local economies.

Bill Gross, the "Bond King" at PIMCO, also blended mathematical approaches with intuition to predict interest rates. Macro investors like George Soros and Stanley Druckenmiller made large profits from a few "gutsy moves" anticipating global shifts, as demonstrated by Soros's massive short against the British pound. It seemed "self-evident" that the surest way to profit was through corporate information and economic trends, making the idea of computers beating these pros "far-fetched".

Kepler Financial and the Nova Fund's Struggles

Robert Frey's Kepler Financial (later Nova), backed by Simons, struggled despite improving on statistical-arbitrage strategies by identifying market-wide factors. Kepler's approach involved buying and shorting stocks based on their sensitivity to underlying factors and deviations from historical norms, aiming for a market-neutral portfolio with a high Sharpe ratio. However, Nova generated "middling results," as its predicted profits often "paled in comparison" to actual gains. Staffers believed Frey's model was too sensitive to market fluctuations, "too much noise in the market for Frey’s system to hear any of its signals". Simons needed "two oddballs" to solve this problem.

Recruiting Peter Brown and Robert Mercer

Nick Patterson, alongside Henry Laufer, took on the task of recruiting talent for Renaissance, favoring "supersmart" individuals with academic accomplishments over Wall Street types. Simons needed to trust that employees, with full access to the firm's source code, wouldn't defect with trade secrets. Patterson's initial letters to Peter Brown and Robert Mercer were discarded.

Robert Mercer's passion for computers began at age ten when his father, Thomas Mercer (a world expert on aerosols), showed him an IBM 650. At Sandia High and University of New Mexico, Mercer excelled in math. A summer at the National Youth Science Camp allowed him extensive access to an IBM 1620, where he learned Fortran, becoming cynical about government-financed research, believing it was more about "consum[ing] the computer budget" than getting answers. After earning his PhD in computer science from the University of Illinois, Mercer joined IBM's speech-recognition group in 1972.

Peter Brown, whose father, Henry Brown, co-founded the world's first money-market mutual fund, joined IBM's speech group in 1984. Brown, Mercer, and Fred Jelinek's team challenged conventional linguistic approaches, viewing language like a game of chance, with probabilities for word sequences. Their goal was to feed computers enough data to develop a "probabilistic, statistical model capable of predicting likely word sequences based on sequences of sounds," using "hidden Markov models" and the Baum-Welch algorithm to "learn from data" rather than manual programming. They relied on Bayesian mathematics, which continuously narrowed possibilities.

Mercer's personality was "laconic, efficient," avoiding words unless necessary, often humming classical music, and sticking to Coca-Cola. He was frugal, eating peanut-butter sandwiches from a reused brown paper bag. Brown was more "animated, approachable, and energetic," but showed impatience and often mocked colleagues, including an intern, Phil Resnik. Meredith Goldsmith, a female colleague, felt "objectified and not taken seriously" due to Mercer's view that "women belonged at home" and Brown's tolerance of "dirty jokes". The group fostered a "fierce and ruthless culture," with intellectual combat and personal jabs, though many didn't take it personally. Despite their breakthroughs in speech recognition (foreshadowing Alexa, Siri), they were frustrated by IBM's lack of commercialization plans.

Mercer's family tragedies in 1993 (mother killed, father died) and Patterson's persistent calls prompted him to reconsider joining Renaissance. He was initially skeptical of hedge funds, but found Renaissance's focus on science appealing. Brown and Mercer were initially split up at Renaissance, but secretly continued to work on a stock-trading model, needing help from David Magerman.

Chapter Ten: David Magerman shut the door of his Boston apartment well before dawn on a cool morning in the fall of 1994.

Magerman's Recruitment and Early Renaissance Experience

David Magerman's job interview at Renaissance in 1994 was challenging; he was exhausted, grilled on an obscure paper, and perceived as immature. However, Peter Brown and Robert Mercer, who knew Magerman from IBM, vouched for his programming skills, recognizing the firm's desperate need for additional firepower. Magerman's strained relationship with his father, a cabbie plagued by bad luck, influenced him, as did his childhood candy-selling business that got him suspended. He was ostracized by wealthier schoolmates, vowing to "enjoy his own wealth one day". He developed a "messiah complex," fighting for justice, even rallying rabbis to cancel a Passover track meet despite not being religious. He later embraced Judaism in Israel, which led his mother to remove references to it in his college essays, except for Penn, which she mistakenly thought was a Jewish university. He thrived at Penn and Stanford, where his doctoral thesis tackled language analysis with statistics, the same problem Brown and Mercer worked on. At IBM, he flourished in the "sharp-elbowed culture," but was rejected by Jenji Mercer, Robert Mercer's daughter.

Magerman joined Renaissance in 1995, finding its offices unimpressive and Simons casually dressed in Bermuda shorts. Simons was disappointed with the "Nova" stock-trading system (Robert Frey's former firm), which was "just limping along". Mercer diagnosed the problem, quoting, "There’s many a slip ’twixt the cup and the lip," meaning Frey's system had brilliant ideas but failed in implementation. Frey eventually shifted to another project. Mercer then won approval to join Brown in stock research, a "last chance" for Simons to grow the firm. Simons pushed, "Guys, let’s make some money".

Brown and Mercer's Breakthrough

The Brown-Mercer reunion was a "new chapter" in their "unusual partnership," balancing Brown's bluntness and energy with Mercer's taciturnity. Brown acknowledged Mercer's deeper influence, as if he was "uncovering some master plan". They dedicated themselves, working late and sharing a living space, to revamping Frey's model. They discovered Frey's model made impractical suggestions, requiring manual overrides for leverage limits. Their solution was to program all limitations and qualifications into a "single trading system" that could automatically handle complications. Being computer scientists, they had the "coding chops" to build a "single automated system for trading stocks". They treated it as a math problem, optimizing decisions to maximize returns based on inputs like trading costs, leverage, and risk.

The "beauty of the approach" was its ability to easily test and add new signals, instantly knowing if gains would top costs. Their system was "adaptive," learning and adjusting on its own, self-correcting if trades weren't executed. It ran an "optimization process" weighing thousands of trades multiple times an hour, issuing electronic instructions. This "secret weapon" would be crucial. Their new stock-trading system had "half a million lines of code," was less sensitive to market fluctuations, and held shares longer, about two days on average. They began reassembling their IBM team, including the Della Pietra twins and Magerman.

Magerman's Impact and Near Disaster

Magerman, eager to be "indispensable," convinced colleagues to switch to C++ (his expertise). He learned the stock-trading tactics rapidly, soaking up compliments from Brown. He then secretly deployed a monitoring tool, "Joshua," a program he had used at IBM to commandeer computers for unauthorized coding. This unleashed a "computer virus" smack in the middle of a trading day, jeopardizing research.

Simons, despite his usual optimism, gave Brown and Mercer an ultimatum: fix the system in six months. Brown worked tirelessly, sleeping in his office, but couldn't find the problem. Magerman, aching to help despite his previous "costly flub," pored over the code. One evening, he spotted a bug: a static S&P 500 figure in the simulation code that was roughly half the current market level, written by Mercer. He fixed this, then an algebraic error. The simulator now recommended an ideal portfolio that seemed to generate "big profits". Brown was skeptical, but Mercer, after patiently reviewing Magerman's work, confirmed the fix. Simons was thrilled, proclaiming, "This is great! Let’s keep it going". This marked a new era for Magerman and the firm.

Chapter Eleven: Money Isn’t Everything

The Roots of Simons's Investing Style

Jim Simons's excitement in late 1990 stemmed from his conviction that historical market patterns could be used to create computer models capable of predicting future trends. This approach, while innovative for its scientific rigor, was not entirely new. Speculators had practiced forms of pattern recognition for centuries. Early examples include Babylonian traders recording crop prices, Christopher Kurz in the 16th century forecasting spice prices using astrological signs and early back-testing, and Munehisa Homma, an 18th-century Japanese rice merchant, who invented charting methods like the "candlestick pattern" and advocated for quick losses and letting profits run.

Evolution of Technical Analysis

The 1830s saw British economists selling sophisticated price charts to investors. Later, American journalist Charles Dow, co-founder of The Wall Street Journal, applied mathematical rigor to market hypotheses, originating modern technical analysis. William D. Gann, an early 20th-century prognosticator, gained a following by claiming to predict market cycles based on the idea that "That which has been is that which shall be...there is nothing new under the sun". Gann believed in a "Law of Vibration" governed by geometric sequences and angles, and his methods remain a branch of technical trading. Despite this, technical traders faced widespread ridicule, being viewed as simplistic or practicing "voodoo science". However, some modern traders still consult charts, and Professor Andrew Lo considers technical analysts the "forerunners" of quantitative investing, though their methods lacked independent testing and often relied on human pattern recognition.

Simons's Approach and Early Quant Pioneers

Simons, like his predecessors, sought patterns and correlations in market data, but aimed for a more scientific approach through rigorous testing and sophisticated predictive models rather than simple chart-watching. He, however, was unaware that others were already making significant progress with similar computer-driven strategies.

The computer age brought early quant efforts. As early as 1965, Barron's magazine praised computers for their potential to revolutionize investing, and The Wall Street Journal highlighted their ability to filter stocks instantaneously. Richard Dennis, known as the "Prince of the Pit" in Chicago, famously trained "turtles" with his trend-following system, reportedly making $80 million in 1986, but suffered heavy losses in 1987.

The Rise of Quants and Market Skepticism

Throughout the 1980s, applied mathematicians and ex-physicists were recruited to Wall Street for "financial engineering," building models for derivatives, risk analysis, and hedging. These specialists became known as "quants," a term initially used pejoratively by traditional finance professionals. Skepticism was fueled by events like the 1987 Black Monday crash, blamed partly on "portfolio insurance" (a hedging technique where computers sold futures, exacerbating the decline). Floyd Norris of The New York Times later criticized this as "the beginning of the destruction of markets by dumb computers". Benoit Mandelbrot's work on fractals in financial markets also reinforced doubts about elaborate computer models, suggesting more unexpected events than models typically predicted.

Edward Thorp: The First Modern Quant

Edward Thorp, a mathematician and associate of Claude Shannon and John Kelly, was the first modern mathematician to use quantitative strategies for significant investments. After gaining fame with his book Beat the Dealer, which outlined systematic gambling tactics, Thorp turned to Wall Street in 1964. He found the financial world surprisingly unsophisticated. Thorp developed a formula to price stock warrants accurately, using a Hewlett-Packard 9830 computer to buy undervalued ones and short expensive ones, thereby protecting his portfolio. His success, featured on the front page of The Wall Street Journal in 1974, made him believe computer models were the only reasonable investing approach. By the late 1980s, his fund, Princeton/Newport, managed nearly $300 million, dwarfing Simons's Medallion fund, but it was crippled by publicity from the Michael Milken junk-bond scandal and closed in 1988.

Other Early Quant Efforts

Morgan Stanley's Gerry Bamberger developed pairs trading, where a database tracked historic prices of paired stocks to profit when their spread returned to normal levels after unusual activity. Nunzio Tartaglia renamed this group Automated Proprietary Trading (APT), adding automation, generating $50 million in annual profits by 1987 without understanding the underlying stocks.

Robert Frey, also from Morgan Stanley, attempted a "factor investing" approach with Simons's backing through Kepler Financial Management. This involved deconstructing stock movements by identifying independent variables (e.g., oil prices, interest rates, market momentum) and betting on deviations from historical relationships, creating a "market neutral" portfolio. Kepler's fund, later called Nova, aimed for a high Sharpe ratio by focusing on reversion-to-the-mean strategies. Despite profitable trade ideas, implementation issues hindered its success, making its profits fall short of predictions.

David Shaw: A Formidable Rival

David Shaw, another quant pioneer, founded D. E. Shaw, hiring diverse PhDs in math and science, including English and philosophy majors, chess masters, and even a demolitions specialist. His firm operated quietly, anticipating the internet's possibilities (Jeff Bezos worked for him). Shaw's fund quickly grew to hundreds of millions, trading equities, but Simons wasn't fully aware of his progress. Simons sought support from Donald Sussman, who was backing Shaw, hoping for a similar boost.

Chapter Twelve: Money Changes Everything

Renaissance's Data Revolution

In 2001, Renaissance began an aggressive expansion of its data collection, aiming to predict stock prices at every future point (three seconds, days, weeks, months). The firm absorbed vast amounts of information, including trade orders (even uncompleted ones), earnings reports, corporate executive stock trades, government reports, economic predictions, news flashes, internet posts, and even obscure data like offshore insurance claims, accumulating a terabyte of data annually. Robert Mercer's mantra became, "There’s no data like more data".

This drive was partly fueled by the realization that trading stocks had similarities to speech recognition, leading Renaissance to recruit heavily from IBM's computational linguistics team. As trading became increasingly electronic, Medallion aimed for a fully automated system with minimal human interaction.

Extraordinary Returns and Tax Strategies

Medallion achieved remarkable success, soaring 98.5% in 2000 and 33% in 2001, significantly outperforming the S&P 500 and rival hedge funds. Its Sharpe ratio, a measure of risk-adjusted returns, reached an astounding 6.0 by early 2003, suggesting almost no risk of annual losses.

Peter Brown, haunted by the losses of early 2000, sought to protect the firm from future market catastrophes. He gained Simons's approval to use more leverage, a strategy amplified through "basket options" with banks. These options allowed Medallion to control significantly more financial instruments per dollar of cash (e.g., $12.50 or even $20 during downturns, compared to competitors' $7). A crucial benefit of basket options was qualifying for lower long-term capital gains tax rates (20% vs. 39.5%), even for trades lasting only days or hours. While some staffers found this "legal but wrong," Renaissance relied on legal advice. The IRS later challenged this, claiming Simons and executives had underpaid $6.8 billion in taxes, a dispute ongoing as of 2019.

The Impact of Wealth and Internal Shifts

The accumulating wealth began to change the firm's culture. Employees, once modest, started enjoying their winnings, with a "Renaissance Riviera" of mansions emerging in Old Field, Long Island. Porsches and Mercedes became common in the parking lot, and some executives even took helicopters to New York City. The immense compensation, which could be millions or tens of millions annually, led some former academics to question their "outsize compensation".

Power dynamics shifted, with Peter Brown and Robert Mercer gaining influence over Henry Laufer. Brown and Mercer's team was known for its intense work ethic, long hours, and Brown's demanding management style, while Laufer's group remained calmer and less urgent. Simons contemplated retirement, appointing Brown and Mercer as co-CEOs, a decision that caused anxiety among employees who found Brown's style difficult and Mercer's taciturn nature unsettling.

Robert Mercer's Growing Influence and Controversial Views

Robert Mercer's personality, already laconic, became more pronounced, often provoking colleagues, especially Nick Patterson, with his iconoclastic and conservative views (e.g., support for the gold standard, gun ownership, skepticism of climate change, and even quantifying government spending on African Americans). His opinions often lacked robust scientific support, leading to debate and concern among colleagues.

The firm's hiring practices also began to shift, bringing in more employees from rival firms, particularly scientists from Russia and Eastern Europe, which some veterans found unsettling.

Internal Conflicts and Departures

David Magerman, never one to hold back, voiced strong opinions about Simons's smoking habit and supported a public campaign to demolish beach cottages owned by some Renaissance employees, including the firm. Simons also increased Medallion's investor fees to 36% and then 44%, eventually kicking out all outside investors by early 2003 to keep all gains for employees. This move, alongside the perceived shift in firm priorities, displeased Magerman and Glen Whitney.

Alexey Kononenko, a talented but challenging Ukrainian mathematician, openly criticized "deadwood" employees and even Brown and Mercer, questioning Simons's reduced presence and large share of profits. This internal grumbling and a "Lord of the Flies" atmosphere led to veteran departures, including Nick Patterson, who left to study the human genome.

The firm faced a crisis when Alexander Belopolsky and Pavel Volfbeyn, two senior scientists, secretly planned to leave for Millennium Management, raising fears that Medallion's source code and secrets would be compromised. Simons was furious, fearing "they stole from us!".

Chapter Thirteen: Money Changes Everything

Simons's New Strategy: RIEF and RIFF

Grappling with personal grief (the death of his son Nicholas) and concerns about employee motivation and the firm's size limitations, Jim Simons sought a new challenge. Medallion, despite its impressive 25% annual gains and soaring Sharpe ratio of 7.5 by 2004, had a size limit because its short-term strategies would suffer if it managed too much capital.

Simons's solution was to launch a new fund, the Renaissance Institutional Equities Fund (RIEF), to utilize longer-term predictive signals and manage significantly more money (potentially $100 billion) without cannibalizing Medallion's returns. RIEF would hold investments for a month or longer, incorporating both Renaissance's pattern-finding tactics and more traditional fundamental strategies like price-earnings ratios and balance sheet analysis. It aimed for steady returns slightly above the market with lower volatility, appealing to large institutions, and charged lower fees (1% management, 10% performance) compared to Medallion's much higher rates.

RIEF launched in summer 2005, attracting $14 billion by 2006, partly due to Medallion's strong track record (38.4% annualized over 15 years). David Dwyer, a sales executive, conducted tours of Renaissance's campus, showcasing its scientists, data group (30+ PhDs cleaning thousands of data feeds), and the massive computer room, emphasizing the firm's mathematical and scientific backbone. Simons, however, occasionally made awkward gaffes during client interactions, such as lighting up a cigarette in a health organization's meeting. Robert Mercer also struggled with client presentations, once mentioning trading "Chrysler" stock even though the company no longer existed, highlighting his focus on quant models over real-world company knowledge. By 2007, RIEF had grown to $35 billion, leading Renaissance to cap new investments and plan for a new futures fund, RIFF.

Legal Battles and The Quant Quake

Simons faced a tense legal confrontation with Israel Englander, head of Millennium Management, over Pavel Volfbeyn and Alexander Belopolsky, the two former Renaissance researchers who had left to join Millennium. Simons believed they had stolen proprietary information, leading to lawsuits and countersuits. Despite Englander's assertion that his hires relied on open-source software, Simons was furious and worried about potential profit erosion and further defections.

By summer 2007, quantitative hedge funds, inspired by Simons, had become dominant. However, in August 2007, a sudden, widespread financial downturn, later dubbed "the quant quake," hit these firms. Smaller quant funds failed, and even major players like AQR Capital Management and Citadel suffered. The cause was attributed to a "fire sale" by at least one quant fund and others slashing borrowing due to struggling mortgage investments.

During this crisis, Simons was at his mother's funeral in Boston. Upon learning of Medallion and RIEF's losses, he initially remained confident, but as losses mounted over days, he grew fearful. Despite Peter Brown and Robert Mercer advocating to "Trust the models" and even "add positions," Simons decided to override the system, stating, "Our job is to survive" and ordering the firm to sell positions to build cash. This decision, made in a moment of intense fear, clashed with his quantitative philosophy. While some Renaissance staffers later complained of lost profits, Simons maintained he would make the same decision again.

Post-Crisis Departures and Performance

Following the quant quake, Glen Whitney and David Magerman left Renaissance, partly due to their dissatisfaction with the firm's handling of internal conflicts and its changing culture.

In contrast to RIEF's struggles (losing 17% in 2008 and 6% in 2009 while the S&P 500 soared), Medallion thrived during the 2008 financial crisis, soaring an astonishing 82%. Simons made over $2 billion in personal profits that year. He was called to testify before Congress, where he supported forcing hedge funds to share information with regulators and advocated for higher taxes on hedge fund managers. However, traditional investors like John Paulson and George Soros, who successfully predicted the subprime crisis with old-fashioned research, overshadowed Simons's quant success in the public eye. RIEF's underperformance in 2008-2009 disillusioned investors who had expected Medallion-like returns, leading Peter Brown to suggest the fund might be discontinued. Simons, meanwhile, prepared to focus on spending his wealth.

Chapter Fourteen: Money Changes Everything

Simons's Philanthropy

Jim Simons, with a net worth of about $11 billion, began dedicating more time to his philanthropy. He owned a 220-foot, $100 million yacht named Archimedes and a $50 million Fifth Avenue apartment. Through the Simons Foundation, he and Marilyn committed over $300 million to institutions like Stony Brook University. Simons focused on two major areas: autism research and mathematics education. He convened top scientists for autism research in 2003, committing $100 million and establishing the Simons Simplex Collection to identify autism-related genes. He also co-founded Math for America in 2004, providing $15,000 annual stipends to over a thousand top math and science teachers in New York City public schools to retain talent in the field. Despite stepping down from an active role at Renaissance, Simons remained its chairman and main shareholder, acknowledging feeling "irrelevant" at times but finding renewed purpose in his philanthropic ventures.

Medallion's Continued Evolution

Medallion continued to thrive, holding thousands of long and short positions with holding periods from days to weeks, and employing high-frequency trades for hedging and position building. The firm emphasized data cleaning, risk management, and precise cost estimation, with Simons noting, "I’m not sure we’re the best at all aspects of trading, but we’re the best at estimating the cost of a trade". By this time, Renaissance employed about 250 staffers, including over sixty PhDs in diverse fields like artificial intelligence, quantum physics, and computational linguistics, and even astronomers who excelled at finding market patterns.

Medallion's profits were driven by complex equity trades and a mixture of signals, including trending and reversion-predicting signals like "Déjà Vu". Robert Mercer famously stated, "We’re right 50.75 percent of the time…but we’re 100 percent right 50.75 percent of the time," emphasizing the power of a slight edge across thousands of simultaneous trades.

A core insight at Renaissance was that investments are influenced by far more factors than commonly understood, including non-obvious and illogical forces. By analyzing hundreds of financial metrics, social media feeds, online traffic, auto insurance applications, and more, they uncovered "multidimensional anomalies" – subtle mathematical relationships between interconnected companies. The key was their "engineering" – the automated system that combined these factors to construct an optimal portfolio, executing trades in unpredictable ways to preserve their signals and "move prices such that competitors couldn’t find them". Simons summarized their approach as "a very big exercise in machine learning," studying the past to predict the future nonrandomly.

Robert and Rebekah Mercer's Political Ascent

Robert Mercer, known for his reclusive nature and preference for cats over humans, also indulged in a $2.7 million model train set. He held strong libertarian views, including disdain for taxes, skepticism of climate change (funding Arthur Robinson's urine stockpile research, which argued low radiation could be beneficial), and belief in minimal government due to perceived incompetence. After Barack Obama's election, Mercer began making sizable political donations, eventually becoming a high-profile right-wing donor driven by ideology rather than seeking favors.

Rebekah Mercer, Robert's second-oldest daughter, became the public face of the family's political strategy. A Stanford graduate, she moved from working at Renaissance to homeschooling her children and running a cookie store. She gained prominence for her lavish real estate purchases and for shifting the family's support from traditional conservative groups like the Koch brothers' Freedom Partners to more controversial causes, including a group opposing a mosque near Ground Zero. In 2011, the Mercers met Andrew Breitbart and, with Steve Bannon, purchased nearly 50% of Breitbart News, which later became popular with the "alt-right".

After Mitt Romney's 2012 loss, the Mercers became disillusioned with the Republican establishment. Rebekah publicly criticized the GOP's data and canvassing operations, advocating for saving America from "socialist Europe". Bannon brokered Mercer's investment in Cambridge Analytica, an analytics firm specializing in advanced data, which Rebekah encouraged family-funded organizations to utilize. Robert Mercer concluded a major political shift was underway, identifying a need for an "outsider" candidate. The Mercers, guided by Bannon, heavily backed Brexit efforts in the UK, with Breitbart News playing a significant role.

The 2016 Presidential Election

In the 2016 US presidential campaign, the Mercers initially supported Ted Cruz but later shifted to Donald Trump after he became the effective nominee. They launched a super PAC against Hillary Clinton, with Kellyanne Conway managing it. As Trump's campaign struggled in summer 2016, Robert Mercer contacted Bannon, who outlined strategies including more TV presence for Conway. Rebekah Mercer confronted Trump directly with The New York Times's negative coverage, urging him to get organized. Bannon was subsequently installed to run the campaign, bringing order and focusing Trump on disparaging Clinton and promoting "America First" nationalism.

Jim Simons, a longtime Democrat supporter, was torn by his colleague's political involvement. He donated heavily to Democratic causes, including $27 million by the end of 2016. Despite his political differences, Simons defended Mercer's right to spend his money as he wished and noted that Mercer's contributions had been crucial to Medallion's breakthroughs. Trump's team expected to lose on Election Day, with internal projections showing a significant deficit. On election night, Simons and other Clinton supporters watched with growing dismay as Trump secured victory.

Chapter Fifteen: Money Changes Everything

Post-Election Fallout at Simons Foundation and Renaissance

The day after Trump's election, Simons Foundation employees gathered, expressing concern about the incoming administration potentially targeting their tax-exempt status due to Simons's support for Clinton. Simons reassured them, urging a focus on their long-term research in autism and understanding the universe's origins.

Robert Mercer, however, was celebratory, preparing for his annual "Villains and Heroes" holiday party at his estate. He continued to wield significant influence in the Trump administration, with Steve Bannon becoming chief strategist and Kellyanne Conway a counselor to the president. Rebekah Mercer also played an active role, advising on cabinet selections and successfully lobbying for Jeff Sessions as attorney general and Jay Clayton for the SEC. She was recognized as "the First Lady of the alt-right" by GQ magazine.

David Magerman's Public Stance and Firing

David Magerman, a registered Democrat but political centrist, was deeply troubled by Trump's policies. He attempted to contact Rebekah Mercer to offer help, but Robert Mercer called instead. Their conversation, while civil, highlighted deep disagreements on climate change, Obamacare, and immigration.

Word of Magerman's criticisms of Mercer reached his boss, leading to a direct confrontation where Mercer accused Magerman of calling him a "white supremacist". Magerman cited Mercer's comments on the Civil Rights Act, which Mercer defended by quoting economist Thomas Sowell's argument that the act "infantilized" African Americans. Magerman was incensed, outlining his concerns about Trump's policies. Despite knowing the risks, Magerman decided to go public, telling The Wall Street Journal that Mercer was using money "I helped him make to implement his worldview" of shrinking government. This led to public backlash against the Mercers, including death threats.

Renaissance faced a dilemma regarding Magerman, as firing him was risky due to his knowledge of the firm's secrets. At a firm poker night, after Magerman attempted to rejoin the game despite having been told to leave, Rebekah Mercer angrily had him physically removed by security. Days later, Renaissance fired Magerman, ending the conflict.

Mercer's Resignation and Continuing Influence

Public anger intensified over Mercer's political activities, particularly from sources like the Baltimore City Fire and Police Employees' Retirement System. Faced with this pressure, Simons, in October 2017, asked Mercer to step down as co-CEO, citing the negative impact on morale. Mercer, appearing sad and hurt, agreed. In a letter, Mercer clarified his political views, stating he supported "conservatives who favor a smaller, less powerful government" and expressed regret for backing Milo Yiannopoulos, an controversial figure. Robert Frey later expressed sympathy for Mercer, noting the disproportionate vilification he faced compared to other politically active billionaires.

Rebekah Mercer continued to face public scrutiny, denying support for "toxic ideologies" and facing controversy over Cambridge Analytica's data practices. Despite the backlash, the Mercers continued their political involvement, albeit in a lower-key manner, with Rebekah vowing not to be "silenced" and expressing a continued commitment to limit government and promote "personal responsibility".

Chapter Sixteen: Never send a human to do a machine’s job.

The Human Element in Quant Investing

In December 2018, as the stock market plummeted, Jim Simons, despite being a pioneer of quantitative investing, felt anxious and called his family's money manager, Ashvin Chhabra, to discuss whether to short stocks. This demonstrated the irony that even the inventor of systematic trading could revert to human intuition during market stress. This highlights why investors traditionally trusted human judgment over models, yet by 2019, confidence in traditional active management had waned, with more money flowing into passive index funds.

The Decline of Traditional Investing Stars and the Rise of Quants

Many traditional investing stars, such as John Paulson, David Einhorn, Bill Gross, and even Warren Buffett, saw their performance wane and clients leave. This decline was attributed to the loss of their "information advantage"; readily available and digitized financial data meant it was "almost impossible to identify facts or figures not fully appreciated by rival investors". Regulatory crackdowns on insider trading also leveled the playing field. The fastest-moving firms, often quants, gained an edge by instantly scouring real-time information, like job listings for drug approvals.

By early 2019, quant investors comprised nearly a third of all stock-market trades, doubling their share since 2013. This dominance translated into immense wealth for quant leaders like Simons ($1.5 billion in 2018), the founders of Two Sigma, Ray Dalio, and Israel Englander. Ken Griffin's extravagant real estate purchases further exemplified this newfound wealth.

The Future of Data and Machine Learning

The advantages of quant firms are expected to expand with the explosion of new data, including "alternative data" from sensors, satellite images, conference call tones, parking lot traffic, and social media. This includes detailed data like sales of farm equipment, cargo bills of lading, cell phone location data in stores, Amazon reviews, and even analyses of FDA commissioner backgrounds to predict drug approvals.

Exponential growth in computing power allows quants to sift through this data, test millions of predictive signals, and use machine-learning engines that continuously learn from successes and failures. Renaissance anticipated this transformation, with its adaptive models serving as a blueprint for dominant companies like Amazon and Netflix.

Limitations and Risks of Quantitative Investing

Despite the enthusiasm, quant investing has limitations. Processing noisy data and finding accurate signals is difficult; some argue picking stocks is harder for a machine than recognizing faces or driving cars. Most quant hedge funds (excluding Renaissance) haven't significantly outperformed traditional firms, partly due to limited pricing histories for stocks. Certain market segments, like troubled debt, remain difficult for algorithmic systems due to reliance on human judgment and negotiations.

Concerns about computerized trading exacerbating market instability are generally overstated. While some momentum-driven quants might intensify downturns, other approaches like "smart beta" and "factor investing" stabilize the market by buying cheap stocks. Moreover, human fear, greed, and panic historically drove volatility, suggesting machines could lead to more stable markets.

Renaissance's Enduring Success and Lessons

By summer 2019, Medallion Fund had achieved average annual gains of 66% before fees and 39% after fees since 1988, with over $104.5 billion in total trading profits. Renaissance managed $65 billion overall and accounted for up to 5% of daily stock-market trading volume.

The firm's success highlights the predictability of human behavior and the value of the scientific method in combating cognitive and emotional biases. Renaissance rigorously tests hypotheses, letting data, not intuition, guide decisions. Its advantage lies in recognizing more factors and overlooked mathematical relationships influencing markets than most, analogous to bees seeing more colors than humans in flowers. Despite this unique expertise, the firm profits on "barely more than 50 percent" of its trades, underscoring the difficulty of beating the market. Renaissance primarily predicts stock moves relative to other stocks or indexes, rather than absolute direction. Elwyn Berlekamp believed that narratives used by investors were dangerous, preferring numbers for stocks, as focusing on news like earnings reports only leads to average results.

After Robert Mercer stepped down, Peter Brown tweaked his management style, leaning on senior staff, which helped stabilize the firm. Simons, at 80 in 2018, remained confident in the firm's continued success, noting that investors are generally happy as long as money is being made. He continued his fitness routine, philanthropy (Simons Foundation's $450 million annual budget), and political donations to Democratic causes. Simons's life presents contradictions: he saved billions in taxes while lamenting public education underfunding, and hired top scientists while criticizing private industry for siphoning talent from schools. However, his philanthropic efforts are dedicated to potentially world-changing causes like autism research and understanding the origins of the universe.

Epilogue

Simons's Final Quests: Autism and the Universe

Approaching his 81st birthday, Jim Simons was deeply engaged in two major, lifelong challenges: understanding and curing autism, and discovering the origins of the universe and life itself. For autism, his foundation established a repository of genetic samples from 2,800 families, accelerating research on the autistic brain and closing in on potential drug treatments that could help up to 20% of those affected. Simons expressed optimism for their success.

For the origins of the universe, Simons recruited Princeton astrophysicist David Spergel, known for measuring the universe's age and composition. He funded a $75 million observatory in Chile's Atacama Desert, a project led by Spergel and Brian Keating (son of James Ax). This observatory, expected to be completed by 2022, aims to find evidence of the Big Bang and cosmic inflation. Simons himself is skeptical of the Big Bang and supports opposing "bouncing model" theories, maintaining an "aesthetically pleasing" belief that "time has gone on forever". He views this quest with a "winner no matter what" attitude – either his instincts are validated, or his team wins a Nobel Prize. He also supports research into how life began and the possibility of extraterrestrial life.

Life Lessons and Legacy

In a March 2019 lecture at MIT, Simons reflected on his career and offered life lessons: "Work with the smartest people you can, hopefully smarter than you...be persistent, don’t give up easily." He also emphasized being "guided by beauty," whether in a company's operation, an experiment's outcome, or a theorem. Simons acknowledged the role of luck in his life and the possibility that intelligent life might be unique to Earth. His family, including his wife Marilyn and grandson, attended the lecture, as Simons concluded, "We’ve had a lot of luck". He is poised to be remembered not only for how he made his fortune but also for what he did with it.