Jim Simons Concepts

The Man Who Solved the Market: How Jim Simons Launched the Quant Revolution

by Gregory Zuckerman · 5 Nov 2019 · 407pp · 104,622 words

with Steve Bannon to upend American politics David Magerman Computer specialist who tried to stop the Mercers’ political activities A TIMELINE OF KEY EVENTS 1938 Jim Simons born 1958 Simons graduates MIT 1964 Simons becomes code breaker at the IDA 1968 Simons leads math department at Stony Brook University 1974 Simons and

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; I knew how the game was played. Subjects, even recalcitrant ones, usually come around. After all, who doesn’t want a book written about them? Jim Simons and Renaissance Technologies, apparently. I wasn’t entirely shocked. Simons and his team are among the most secretive traders Wall Street has encountered, loath to

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and prescience, Simons was blindsided by much that took place in his life. That may be the most enduring lesson of his remarkable story. PROLOGUE Jim Simons wouldn’t stop calling. It was the fall of 1990 and Simons was in his office on the thirty-third floor of a midtown Manhattan

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really gone too far, Berlekamp thought. Such enormous returns weren’t likely, he told Simons. And you really don’t need to call so much, Jim. Simons couldn’t stop, though. Eventually, it all became too much—Berlekamp quit, a fresh blow for Simons. “The hell with it, I’m just going

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it harder than he expected. CHAPTER THREE Getting fired can be a good thing. You just don’t want to make a habit of it. Jim Simons Weeks after leaving Stony Brook University’s expansive, tree-lined campus in the early summer of 1978, Simons found himself just a few miles down

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or reason.” Simons had to find a different approach. CHAPTER FOUR Truth . . . is much too complicated to allow for anything but approximations. John von Neumann Jim Simons was miserable. He hadn’t abandoned a flourishing academic career to deal with sudden losses and grumpy investors. Simons had to find a different method

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markets, Simons would have to overcome a series of imposing obstacles that he didn’t even realize were in his way. 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

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much interest among the Morgan Stanley brass for their innovative factor approach. “They told me not to rock the boat,” Frey recalls. Frey quit, contacting Jim Simons and winning his financial backing to start a new company, Kepler Financial Management. Frey and a few others set up dozens of small computers to

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hedge fund minted money. Soon, it was managing several hundred million dollars, trading an array of equity-related investments, and boasting over one hundred employees. Jim Simons didn’t have a clear understanding of the kind of progress Shaw and a few others were making. He did know, if he was going

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Sussman, the financier who had given David Shaw the support he needed to start his own hedge fund, hoping for a similar boost. CHAPTER EIGHT Jim Simons’s pulse quickened as he approached Sixth Avenue. It was a sultry summer afternoon, but Simons wore a jacket and tie, hoping to impress. He

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seemed Simons was wasting his time. CHAPTER NINE No one ever made a decision because of a number. They need a story. Daniel Kahneman, economist Jim Simons seemed to have discovered the perfect way to trade commodities, currencies, and bonds: predictive mathematical models. Yet, Simons knew, if he wanted Renaissance Technologies to

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market was by unearthing corporate information and analyzing economic trends. The idea that someone could use computers to beat these seasoned pros seemed far-fetched. Jim Simons, still struggling to make money trading stocks, didn’t need any reminder. Kepler Financial, the company launched by former Morgan Stanley math and computer specialist

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same way—depositing Patterson’s letter in the closest trash receptacle. They’d reconsider after experiencing family upheaval, laying the groundwork for dramatic change at Jim Simons’s company, and the world as a whole. * * * = Robert Mercer’s lifelong passion had been sparked by his father. A brilliant scientist with a dry

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about the “hidden” sequences of words that could have generated those sounds. To do that, the IBM researchers employed the Baum-Welch algorithm—codeveloped by Jim Simons’s early trading partner Lenny Baum—to zero in on the various language probabilities. Rather than manually programming in static knowledge about how language worked

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Island, arriving for a job interview at Renaissance Technologies’ offices in Stony Brook before ten a.m. Magerman seemed a shoo-in for the position. Jim Simons, Henry Laufer, Nick Patterson, and other staffers were acclaimed mathematicians and theoreticians, but Renaissance was starting to develop more-complex computer-trading models, and few

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,” Simons boomed at a weekly meeting. “Let’s keep it going.” A new era for both Magerman and the firm seemed within reach. CHAPTER ELEVEN Jim Simons walked the halls, full of nervous energy. It was the summer of 1997, and Simons sensed he might be close to something special. His Medallion

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the firm in ways Simons and his colleagues never could have anticipated. PART TWO Money Changes Everything CHAPTER TWELVE Something unusual was going on at Jim Simons’s hedge fund in 2001. Profits were piling up as Renaissance began digesting new kinds of information. The team collected every trade order, including those

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flying under the radar of most in the investing world. As the Institutional Investor article in 2000 said, “Chances are you haven’t heard of Jim Simons, which is fine by him. Nor are you alone.”2 Still, Brown and Mercer’s system worked so well that researchers could test and develop

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him. Simons had to find a way to deal with it all. CHAPTER THIRTEEN All models are wrong, but some are useful. George Box, statistician Jim Simons faced a growing list of problems. He had one possible solution. Staffers were squabbling, and two key scientists had bolted, possibly taking Medallion’s secrets

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habitat. “In that conference room, our scientists review their latest predictive signals.” Ooh. “That’s where the crucial peer-review process happens.” Aah. “Over there, Jim Simons meets with his top executives to map strategy.” Wow! As the visitors passed the kitchen area, mathematicians sometimes wandered by to toast a bagel or

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!” Simons flashed a smile, proud he’d figured out a most relevant scientific problem. * * * = Glen Whitney wasn’t nearly as relaxed. After the dinner at Jim Simons’s home where it was decided that Alexey Kononenko wouldn’t be punished for his behavior, Whitney became dejected. He and Magerman had promised they

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,” Brown said. As for Simons, he had devoted more than two decades to building remarkable wealth. Now he was going to spend it. CHAPTER FOURTEEN Jim Simons liked making money. He enjoyed spending it, too. Stepping down from Renaissance gave Simons—who, by then, was worth about $11 billion—more time on

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there is only one person who can save it. We, and Americans across the country and around the world, stand steadfastly behind Donald J. Trump.” * * * = Jim Simons was torn. Ever since he and his childhood friend, Jim Harpel, had driven across the country and witnessed some of the hardships experienced by minorities

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watched Trump seal the election. Before midnight, they turned the television off. They’d seen enough. “We were pretty depressed,” Lackman says. CHAPTER FIFTEEN When Jim Simons looked up, there were dozens of anxious faces staring at him. It was the morning of November 9, 2016, the day after the presidential election

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. CHAPTER SIXTEEN Never send a human to do a machine’s job. Agent Smith in the film The Matrix The stock market was collapsing and Jim Simons was worried. It was late December 2018, and Simons and his wife, Marilyn, were at the Beverly Hills Hotel visiting family in the Los Angeles

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Chase puts hundreds of its new investment bankers and investment professionals through mandatory coding lessons. Simons’s success had validated the field of quantitative investing. “Jim Simons and Renaissance showed it was possible,” says Dario Villani, a PhD in theoretical physics who runs his own hedge fund. The goal of quants like

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even breakthroughs, perhaps during his lifetime. Simons could be remembered for what he did with his fortune, as well as how he made it. EPILOGUE Jim Simons dedicated much of his life to uncovering secrets and tackling challenges. Early in life, he focused on mathematics problems and enemy codes. Later, it was

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, she soothed, cheered, and encouraged me. I appreciate you more each day. My book is dedicated to my sons, Gabriel Benjamin and Elijah Shane. Even Jim Simons couldn’t have developed a model capable of predicting the happiness you’ve given me. APPENDIX 1 Net Returns Management Fee* Performance Fee Returns Before

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managed approximately $55 billion as of April 30, 2019. (Source: Medallion annual reports; investors) APPENDIX 2 Returns Comparison Investor Key Fund/Vehicle Period Annualized Returns* Jim Simons Medallion Fund 1988–2018 39.1% George Soros Quantum Fund 1969–2000 32%* Steven Cohen SAC 1992–2003 30% Peter Lynch Magellan Fund 1977–1990

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/behind-the-market-swoon-the-herdlike-behavior-of-computerized-trading-11545785641. Chapter One 1. D. T. Max, “Jim Simons, the Numbers King,” New Yorker, December 11, 2017, https://www.newyorker.com/magazine/2017/12/18/jim-simons-the-numbers-king. 2. James Simons, “Dr. James Simons, S. Donald Sussman Fellowship Award Fireside Chat Series

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, https://www.nytimes.com/2011/07/19/nyregion/john-s-toll-dies-at-87-led-stony-brook-university.html. 4. James Simons, “Simons Foundation Chair Jim Simons on His Career in Mathematics,” interview by Jeff Cheeger, Simons Foundation, September 28, 2012, https://www.simonsfoundation.org/2012/09/28/simons-foundation-chair

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-jim-simons-on-his-career-in-mathematics. 5. Simons, “On His Career in Mathematics.” Chapter Three 1. Simons, “Mathematics, Common Sense, and Good Luck.” 2. William Byers,

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Press, 2007). 3. Private papers from Lenny Baum, provided by his family. 4. Richard Teitelbaum, “The Code Breaker,” Bloomberg Markets, January 2008. 5. James Simons, “Jim Simons Speech on Leonard E. Baum” (speech, Leonard E. Baum Memorial, Princeton, NJ, August 15, 2017), https://www.youtube.com/watch?v=zN0ah7moPlQ. 6. Simons, “On

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His Career in Mathematics.” 7. Simons, “Jim Simons Speech on Leonard E. Baum.” Chapter Four 1. Byers, How Mathematicians Think. Chapter Five 1. James R. Hagerty and Gregory Zuckerman, “Math Wizard Elwyn Berlekamp

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, October 2013), http://cs.jhu.edu/~post/bitext. Chapter Eleven 1. Hal Lux, “The Secret World of Jim Simons,” Institutional Investor, November 1, 2000, https://www.institutionalinvestor.com/article/b151340bp779jn/the-secret-world-of-jim-simons. 2. Robert Mercer interviewed by Sharon McGrayne for her book, The Theory Would Not Die: How Bayes’ Rule

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a Good Bet for Stock-Market Predictions,” Wall Street Journal, August 8, 2009, https://www.wsj.com/articles/SB124967937642715417. 5. Lux, “The Secret World of Jim Simons.” 6. Robert Lipsyte, “Five Years Later, A Female Kicker’s Memorable Victory,” New York Times, October 19, 2000, https://www.nytimes.com/2000/10/19

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: How Bayes’ Rule Cracked the Enigma Code, Hunted Down Russian Submarines, and Emerged Triumphant from Two Centuries of Controversy. 2. Lux, “The Secret World of Jim Simons.” 3. Abuse of Structured Financial Products (statement of Peter Brown). 4. Katherine Burton, “Inside a Moneymaking Machine Like No Other,” Bloomberg, November 21, 2016, https

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Jenny Strasburg, “Simons Questioned by Investors,” Wall Street Journal, May 15, 2009, https://www.wsj.com/articles/SB124235370437022507. Chapter Fourteen 1. Alice Walker, “Billionaire Mathematician Jim Simons Parks £75 million Super Yacht during Tour of Scotland,” Scottish Sun, July 15, 2018, https://www.thescottishsun.co.uk/fabulous/2933653

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/jim-simons-super-yacht-billionaire-scotland-tour. 2. Simons, “On His Career in Mathematics.” 3. Van Zuylen-Wood, “The Controversial David Magerman.” 4. Ryan Avent, “If It

The Quants

by Scott Patterson · 2 Feb 2010 · 374pp · 114,600 words

hedge fund, Saba (Hebrew for “wise grandfather”), into one of the most powerful credit-trading funds on the planet, juggling $30 billion worth of positions. Jim Simons, the reclusive, highly secretive billionaire manager of Renaissance Technologies, the most successful hedge fund in history, whose mysterious investment techniques are driven by scientists poached

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his age, a wiry Pat Boone in his prime, radiated the relaxed cool of a man accustomed to victory. He waved across the room to Jim Simons, billionaire math genius and founder of the most successful hedge fund on the planet, Renaissance Technologies. Simons, a balding, white-bearded wizard of quantitative investing

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, had started with $1 billion in 1998. By mid-2007, its assets under management neared $40 billion. Citadel’s kitty topped $20 billion. In 2005, Jim Simons announced that Renaissance would launch a fund that could juggle a record $100 billion in assets. Boaz Weinstein, just thirty-three, was wielding roughly $30

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in profits, other funds started trying to copy its superfast trading style. Robert Frey, who’d worked as an APT researcher, took stat arb to Jim Simons’s fund, Renaissance Technologies, in the early 1990s. Peter Muller, the singing quant who triumphed at Wall Street Poker Night in 2006, appeared on the

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was becoming increasingly quantitative, and more and more mathematicians were migrating to Wall Street, inspired by Thorp and fresh waves of research sprouting from academia. Jim Simons’s firm Renaissance Technologies was launching its soon-to-be-legendary Medallion Fund. David Shaw was setting up shop over a communist bookstore in Greenwich

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at a stoplight. In 1989, Muller got an assignment to do some work for a new BARRA client, a hedge fund operator called Renaissance Technologies. Jim Simons was looking for expert help to solve a thorny problem he faced with one of his funds named Medallion. The problem involved the most efficient

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code. One thing was certain: Simons wasn’t talking. By the late 1990s, Ken Griffin was swapping convertible bonds from a high tower in Chicago. Jim Simons was building his quant empire in East Setauket. Boaz Weinstein was scouring computer screens to trade derivatives for Deutsche Bank. Peter Muller was trading stocks

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matched and at times even outpaced Renaissance’s Medallion fund. In 1997, however, Medallion’s returns leapt to a new dimension. The gains were unbelievable. Jim Simons had left everyone behind, and no one knew how he’d done it. Eventually, Renaissance stopped trading through Morgan, concerned that Muller’s operation was

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than 20 percent. In East Setauket, Renaissance’s Medallion fund was getting pummeled, as was the Renaissance Institutional Equity Fund, the massive quant fundamental fund Jim Simons had once said could handle $100 billion in assets. The losses in Medallion, however, were the most perplexing. Simons had never seen anything like it

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related to U.S. housing loans, which had “made it impossible to value certain assets fairly regardless of their quality or credit rating.” Late Thursday, Jim Simons had issued a rare midmonth update on the state of one of his funds. The Renaissance Institutional Equities Fund, which managed about $26 billion in

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, possibly the biggest annual return for an investor ever. The other two managers arrayed before Waxman’s House Committee on Oversight and Government Reform were Jim Simons and Ken Griffin. The quants had come to Capitol Hill. Griffin, for one, had prepared for his appearance with Citadel’s typical discipline. Having flown

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that year. Renaissance’s Medallion fund gained an astonishing 80 percent in 2008, capitalizing on the market’s extreme volatility with its lightning-fast computers. Jim Simons was the hedge fund world’s top earner for the year, pocketing a cool $2.5 billion. Medallion’s phenomenal surge in 2008 stunned the

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walledoff segments of the fund to employees—allows for the chance for breakthroughs that keep Medallion’s creative juices flowing. Insiders also credit their leader, Jim Simons. Charismatic, extremely intelligent, easy to get along with, Simons had created a culture of extreme loyalty that encouraged an intense desire among its employees to

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unless he absolutely needed to. But he had one thing to look forward to: poker. And when it came to poker, Muller was all business. Jim Simons, now seventy-one years old, was in attendance, hunched over a crowded dining table in a blue blazer and gray slacks, philosophically stroking his scraggly

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-fast trading that had become a central component of the Money Grid, strategies first devised in the 1980s by innovators such as Gerry Bamberger and Jim Simons and furthered in the following decade by the likes of David Shaw and Peter Muller. But there were legitimate concerns that as computer-driven trading

Dark, Salt, Clear: Life in a Cornish Fishing Town

by Lamorna Ash · 1 Apr 2020 · 319pp · 108,797 words

: Cecil Richards, W. (Swell) Richards, skipper, J. S. (Jimmy Strick) Matthews, Ben Batten, J. P. (Sailor Joe) Harvey; W. (Billy Bosun) Roberts (a preacher), J. (Jim) Simons, J. H. (Jan Enny) Tonkin and W.H. (Skinny) Williams. The Rosebud, owned by the Richards’ brothers, was to be the chosen vessel. Three days

Adaptive Markets: Financial Evolution at the Speed of Thought

by Andrew W. Lo · 3 Apr 2017 · 733pp · 179,391 words

very long. Today’s financial markets are still distant from a theoretical end-state of perfectly efficient markets. Investors as different as Warren Buffett and Jim Simons consistently out-earn the index funds favored by the Efficient Markets Hypothesis, despite their very different investment strategies. Unlike the Efficient Markets Hypothesis, the Adaptive

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at large scale? I have a two-part answer to these questions. The first answer depends on who “you” are. If you’re David Shaw, Jim Simons, or George Soros, then we already know the answer from chapter 7: the answer is yes. They can beat the market and they have. By

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and financially riskier. This seems really counterintuitive, especially in the investment world where getting smarter usually means less risk and greater profits—think Warren Buffett, Jim Simons, and David Shaw. Not so in biomedicine. Here’s an example. In recent years, scientists discovered that certain medicines are extremely effective when used together

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Leibowitz, Judy Lewent, Steve List, Philippe Lüdi, Saman Majd, Pete Martin, Paul Mende, David Modest, Victor Niederhoffer, John Perry, Jon Roberts, Eric Rosenfeld, David Shaw, Jim Simons, Rob Sinnott, Roger Stein, Andre Stern, Cheng Chih Sung, Donald Sussman, Phil Vasan, Duncan Wilkinson, Jake Xia, and Xiru Zhang. And from the public sector

Nobody's Fool: Why We Get Taken in and What We Can Do About It

by Daniel Simons and Christopher Chabris · 10 Jul 2023 · 338pp · 104,815 words

might unjustifiably conclude that we had discovered a brilliant investor. To be clear, we aren’t saying that investors like Peter Lynch, Ray Dalio, and Jim Simons owe their success to luck alone—only that when thinking about success stories, we should keep in mind that most of what we hear is

More Money Than God: Hedge Funds and the Making of a New Elite

by Sebastian Mallaby · 9 Jun 2010 · 584pp · 187,436 words

shop; a man who collects plastic superheroes is not going to remain a salaried antihero for long, at least not if he can help it. Jim Simons of Renaissance Technologies, the mathematician who emerged in the 2000s as the highest earner in the industry, would not have lasted at a mainstream bank

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who owned a piece of Ford could always count on getting a fair price for it. By computerizing Steinhardt’s art, statistical arbitrageurs such as Jim Simons and David Shaw were taking his mission to the next level. The more markets could be rendered efficient, the more capital would flow to its

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only part of the challenge. The next question was how much to bet on each position. Short-term trading systems like the one that powered Jim Simons’s Medallion Fund also confronted this problem, but in a different way: Because they were operating on short time frames, they risked moving the price

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stable. Otherwise they would begin a death spiral. Meanwhile, versions of this drama were playing out at other quantitative hedge funds. Most were not like Jim Simons’s Medallion: They were trading well-known price anomalies, not esoteric secrets; “there is no E=MC2 under the hood,” as Asness put it.30

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off torpedoes at every other quant; there were rumors of funds that were down 10 percent or worse. At the Renaissance campus in Long Island, Jim Simons huddled with his top lieutenants in front of the computer screens, tweaking the parameters on his models like a pilot navigating a hurricane. Cliff Asness

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markets—anybody who might know anything about how other leveraged quant funds were positioned. The business was dominated by a handful of firms. There was Jim Simons’s new fund, which ran more than $25 billion of institutional money. There was Highbridge Capital, a subsidiary of J.P. Morgan. There were D

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. Simons’s connection to Baum also helped him persuade Brown and Mercer to join up. Peter Brown recalls: “When Bob and I were contacted by Jim Simons we hadn’t heard of him. But when we heard he had worked with Lenny Baum we started to take the offer seriously.” Peter Brown

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how a convertible bond portfolio could be.” 11. A senior Amaranth executive recalls, “Nick was always very jealous of, envious, as we all are, of Jim Simons’s ability to manufacture money with the Medallion fund. We spent a lot of money building stat-arb systems, hiring stat-arb people. Didn’t

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: Questions and Answers about the Crash and Subsequent Rebound of Quantitative Stock Selection Strategies,” working paper, September 21, 2007.) In an e-mail to investors, Jim Simons wrote, “While we believe we have an excellent set of predictive signals, some of these are undoubtedly shared by a number of long/short hedge

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funds.” (Jim Simons, e-mail to Renaissance Technologies investors, August 9, 2007.) 32. Satya Pradhuman, director of research at Cirrus Research, identified 148 companies with market capitalizations between

The Physics of Wall Street: A Brief History of Predicting the Unpredictable

by James Owen Weatherall · 2 Jan 2013 · 338pp · 106,936 words

money manager is a man you’ve probably never heard of — unless you’re a physicist, in which case you’d know his name immediately. Jim Simons is co-inventor of a brilliant piece of mathematics called the Chern-Simons 3-form, one of the most important parts of string theory. It

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their losses by the end of the year. On average, hedge funds returned about 10% in 2007 — less than many other, apparently less sophisticated investments. Jim Simons’s Medallion Fund, on the other hand, returned 73.7%. Still, even Medallion had felt the August heat. As 2008 dawned, the quants hoped the

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ever, of about 10% book value per share — while the shares themselves halved in value. But not everyone was a loser for the year. Meanwhile, Jim Simons’s Medallion Fund earned 80%, even as the financial industry collapsed around him. The physicists must be doing something right. 1 Primordial Seeds LA FIN

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known as gauge theory. (The early mathematical development of modern gauge theory — the topic on which Weinstein wrote his dissertation — was largely the work of Jim Simons, the mathematical physicist turned hedge fund manager who founded Renaissance Technologies in the 1980s.) Gauge theories use geometry to compare apparently incomparable physical quantities. This

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the gauge revolution. Beginning in 1961, fundamental physics was rewritten in terms of gauge theory — a process that only accelerated when Yang, in collaboration with Jim Simons of Renaissance, realized a deep connection between Yang-Mills gauge theories and modern geometry later that decade. Gauge theories proved particularly important in physics because

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again that just as O’Connor survived the 1987 crash by being a little more sophisticated in how it used its models than anyone else, Jim Simons’s Renaissance Technologies returned 80% in 2008 — again by being smarter than the competition. What’s the difference between Renaissance and other hedge funds? It

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Burton 2008). “. . . promoted by Nassim Taleb . . .”: See Taleb (2004, 2007a). “Even the traditionalists suffered . . .”: Numbers are from Berkshire Hathaway’s 2010 annual report (Buffett 2010). “Jim Simons’s Medallion Fund . . .”: The Medallion numbers are from Willoughby (2009). 1. Primordial Seeds “Or so it would have seemed to Louis Bachelier . . .”: The story told

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gauge theory”: For more on the history of gauge theory, including Weyl’s early contributions, see O’Raifeartaigh (1997). “. . . accelerated when Yang, in collaboration with Jim Simons . . .”: Simons and Yang describe their collaboration in Zimmerman (2009); see also the famous Wu-Yang dictionary (Wu and Yang 1975). “This framework was called the

Other People's Money: Masters of the Universe or Servants of the People?

by John Kay · 2 Sep 2015 · 478pp · 126,416 words

successful record in investment banks established their own operations. Some hedge fund managers made extraordinary sums. George Soros has reported wealth of $26.5 billion: Jim Simons, a former mathematics professor, $15.5 billion.12 The reward for traders within banks increased, substantially if not commensurately, as these companies tried to keep

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capital firms) specialise in the provision of finance for business. Specialist hedge funds – tightly run speculative trading ventures such as those of George Soros and Jim Simons – attracted funds in the years after 2000. But, apparently paradoxically, the trend to specialisation was accompanied by a trend to diversification. Regulation Q, which restricted

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make returns from minute movements in the prices of securities. The most persistently successful of these quantitative-oriented funds are the Renaissance Technologies funds of Jim Simons, which have over more than two decades earned extraordinary returns for investors while charging equally extraordinary levels of fee. Simons was a distinguished mathematician before

The Aristocracy of Talent: How Meritocracy Made the Modern World

by Adrian Wooldridge · 2 Jun 2021 · 693pp · 169,849 words

brain power: computer geeks such as Bill Gates (Microsoft) and Mark Zuckerberg (Facebook) or financial wizards such as George Soros (who pioneered hedge funds) and Jim Simons (who helped to found computer-driven ‘quant investing’).9 The world’s richest man, Jeff Bezos, graduated summa cum laude and Phi Beta Kappa from

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/content_34115212.htm 7 Sandel, The Tyranny of Merit, p. 107 8 Ibid., p. 84 9 Gregory Zuckerman, The Man Who Solved the Market: How Jim Simons Launched the Quant Revolution (New York, Portfolio, 2019) 10 ‘America’s New Aristocracy’, Economist, 22 January 2015 11 Peter Saunders, Social Mobility Myths (London, Civitas

Radical Uncertainty: Decision-Making for an Unknowable Future

by Mervyn King and John Kay · 5 Mar 2020 · 807pp · 154,435 words

making similar decisions arise often, and the outcomes are clear. So it is possible to learn from long runs of successful results; hedge fund manager Jim Simons’ trading algorithms have been – overall – very profitable. We may perhaps learn even more from long runs of unsuccessful results, although few traders are given the

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but actively contributed to it. Another is to look at the achievements of the most successful investors of the era – Warren Buffett, George Soros and Jim Simons. Each has built fortunes of tens of billions of dollars. They are representative of three very different styles of investing. Buffett’s investment company, Berkshire

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of the college endowment – might not be realised. The efficient market hypothesis, taken literally, implies that the investment success of George Soros, Warren Buffett and Jim Simons is impossible. Frank Knight, who recognised that radical uncertainty generates profit opportunities, has been vindicated by the extraordinary riches accumulated by these men. And the

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(Cambridge, Massachusetts: HUP, 2002) Lucas, R. E., ‘Macroeconomic Priorities’, American Economic Review , Vol. 93, No. 1 (2003), 1–14 Lux, H., ‘The Secret World of Jim Simons’, Institutional Investor (1 Nov 2000) MacIntyre, A., After Virtue: A Study in Moral Theory (London: Gerald Duckworth and Co., 2003) Mackay, C., Extraordinary Popular Delusions