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The Man Who Solved the Market: How Jim Simons Launched the Quant Revolution
Gregory Zuckerman, the bestselling author of The Greatest Trade Ever and The Frackers, answers the question investors have been asking for decades: How did Jim Simons do it?
Shortlisted for the Financial Times/McKinsey Business Book of the Year Award
Jim Simons is the greatest money maker in modern financial history. No other investor--Warren Buffett, Peter Lynch, Ray Dalio, Steve Cohen, or George Soros--can touch his record. Since 1988, Renaissance's signature Medallion fund has generated average annual returns of 66 percent. The firm has earned profits of more than $100 billion; Simons is worth twenty-three billion dollars.
Drawing on unprecedented access to Simons and dozens of current and former employees, Zuckerman, a veteran Wall Street Journal investigative reporter, tells the gripping story of how a world-class mathematician and former code breaker mastered the market. Simons pioneered a data-driven, algorithmic approach that's sweeping the world.
As Renaissance became a market force, its executives began influencing the world beyond finance. Simons became a major figure in scientific research, education, and liberal politics. Senior executive Robert Mercer is more responsible than anyone else for the Trump presidency, placing Steve Bannon in the campaign and funding Trump's victorious 2016 effort. Mercer also impacted the campaign behind Brexit.
The Man Who Solved the Market is a portrait of a modern-day Midas who remade markets in his own image, but failed to anticipate how his success would impact his firm and his country. It's also a story of what Simons's revolution means for the rest of us.
Shortlisted for the Financial Times/McKinsey Business Book of the Year Award
Jim Simons is the greatest money maker in modern financial history. No other investor--Warren Buffett, Peter Lynch, Ray Dalio, Steve Cohen, or George Soros--can touch his record. Since 1988, Renaissance's signature Medallion fund has generated average annual returns of 66 percent. The firm has earned profits of more than $100 billion; Simons is worth twenty-three billion dollars.
Drawing on unprecedented access to Simons and dozens of current and former employees, Zuckerman, a veteran Wall Street Journal investigative reporter, tells the gripping story of how a world-class mathematician and former code breaker mastered the market. Simons pioneered a data-driven, algorithmic approach that's sweeping the world.
As Renaissance became a market force, its executives began influencing the world beyond finance. Simons became a major figure in scientific research, education, and liberal politics. Senior executive Robert Mercer is more responsible than anyone else for the Trump presidency, placing Steve Bannon in the campaign and funding Trump's victorious 2016 effort. Mercer also impacted the campaign behind Brexit.
The Man Who Solved the Market is a portrait of a modern-day Midas who remade markets in his own image, but failed to anticipate how his success would impact his firm and his country. It's also a story of what Simons's revolution means for the rest of us.
359 pages, Paperback
First published November 5, 2019
About the author
Gregory Zuckerman
10 books336 followersGregory Zuckerman is a Special Writer at The Wall Street Journal, a 25-year veteran of the paper and a three-time winner of the Gerald Loeb award -- the highest honor in business journalism.
Greg is the author of six books: A Shot to Save the World: The Inside Story of the Life-or-Death Race for a COVID-19 Vaccine; The Man Who Solved the Market: How Jim Simons Launched the Quant Revolution; The Frackers: The Outrageous Inside Story of the New Billionaire Wildcatters; The Greatest Trade Ever: The Behind-the-Scenes Story of How John Paulson Defied Wall Street and Made Financial History; Rising Above: How 11 Athletes Overcame Challenges in Their Youth to Become Stars and Rising Above: Inspiring Women in Sports.
Greg lives with his wife and two sons in West Orange, N.J., where they enjoy the Yankees in the summer, root for the Giants in the fall, and reminisce about Linsanity in the winter.
Greg is the author of six books: A Shot to Save the World: The Inside Story of the Life-or-Death Race for a COVID-19 Vaccine; The Man Who Solved the Market: How Jim Simons Launched the Quant Revolution; The Frackers: The Outrageous Inside Story of the New Billionaire Wildcatters; The Greatest Trade Ever: The Behind-the-Scenes Story of How John Paulson Defied Wall Street and Made Financial History; Rising Above: How 11 Athletes Overcame Challenges in Their Youth to Become Stars and Rising Above: Inspiring Women in Sports.
Greg lives with his wife and two sons in West Orange, N.J., where they enjoy the Yankees in the summer, root for the Giants in the fall, and reminisce about Linsanity in the winter.
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May 29, 2020
The Philosophy of Financial Markets
There are essentially two ways, two visions, two philosophies, of conducting inquiry in the social sciences. In one, rational behaviour is defined by some plausible propositions; behavioural data are then analysed; and people are shown to often act irrationally. In the other philosophy, the observed patterns of human behaviour are used to define an implicit standard of rationality which may be hidden and even unconscious. These patterns (or ‘signals’) are then used to predict future states. The first is an example of the philosophy of Rationalism, which holds that laws precede and produce facts. The second is an example of Empiricism, which claims that facts precede and produce laws. The intellectual battle about which of these views is better is ancient and still hasn’t been resolved - not just in the social sciences, but also in all scientific inquiry.
Within the social sciences, financial economists are generally Rationalists. They create models of economic choice which they then use to judge the rationality (which they call efficiency) of markets, and sometimes to exploit what they find to be irrational behaviour by buying or selling to correct the situation (making the market more efficient makes money, a win/win for the individual and society, they believe). Financial chartists (or technical analysts if one prefers) are Empiricists. They look for patterns (‘structure’ in the jargon) in the movements of markets prices from which they attempt to predict future prices (chartists don’t apologise; they are in it for the money). Financial economists and chartists view each other as fools and hucksters. Economists point to the absence of chartists’ theory as proof of their irrationality. Chartists claim the lack of theory as a virtue and deride the economists ignorance of the real world. They don’t want to second-guess the market, only to understand its inherent rationality.
Historically, Rationalist financial economists had the upper hand in academic circles and among the big names in financial trading.* Beginning in the early 1950’s, its influence grew rapidly as it was taught to generations of MBA’s who spread it like an infection throughout the world. The bias toward rationalism was so pervasive that it was the primary cause of the 2007 financial crisis, which demonstrated just how irrational rationality could be. In the way of these things, fashions changed in the perennial attempt to beat the market. Empiricism was in; Rationalism was out. Old-fashioned chartism entered the realm of Artificial Intelligence and became respectable (hence the euphemism of ‘technical analysis’).
And the new chartism works. No one knows why it works. It just does, as Jimmy Simons and Robert Mercer discovered to their enormous personal benefit. Neither knows all that much about financial markets, but they know about data, raw information from a staggering array of sources, within which are hidden patterns like the traces of gold at Sutters Creek or like intelligible messages buried within the gobbledygook of an enemy code. Markets didn’t need a theory; they provide their own theory if one pays enough attention to the detail. And computer technology was just the tool that was needed to sift, sort, and correlate all the detailed data one might collect in the search for the El Dorado of financial trading.
Financial economics worked, while it worked, largely because big investors felt compelled by academic theory to act rationally. Fund managers, banks, and other fiduciaries had a duty to act rationally on behalf of their clients. In the absence of any plausible alternative, professional ethics demanded adoption of the theory. The theory, therefore, became a self-fulfilling prophecy - and the prophecies came true until the world discovered that its rationality was no more than a conventional fiction. By avoiding the intellectual arrogance of presuming it knows better than the market, the new chartists can claim to be grounded in reality not economic fantasy.
The problem of course is that no one knows why the various correlations, connections, and intersections of data work (when they do). Empiricists don’t usually look for reasons. And when they do, it is typically to rationalise the conclusions their algorithms have already produced.** The algorithms which manipulate the data may contain an implicit theory but that doesn’t really bother the Empiricist. Nor does the lack of reasons for the various correlations. Coincidence or cause, the empiricist isn’t worried. What he does worry about is someone stealing his proprietary algorithms. The Rationalist benefits by the widespread use of his theory; the Empiricist by the strict secrecy of his programmes.***
Therein lies the Empiricist’s Achilles Heel. There is literally no reason to believe his correlations are stable. There is no way to test or verify hypotheses. Technically, there are no hypotheses. And no one aside from the proprietor is checking the validity of the findings of inquiry (thus violating a fundamental principle of true scientific inquiry). Correlations may change randomly and without warning. The enemy code, if there is one, might be altered entirely from day to day. Investors who employ the chartist strategy will never know if they are, quite literally, entering uncharted territory. On the other hand, society is considerably safer in the hands of chartists, as long as they act independently of each other based on their own algorithms (something the old-fashioned chartists did not do). Some may win while others loose; but they’re unlikely to all win or lose together, thus provoking systematic misery. That, however, until enough big investors discover similar correlations and interpret them as signals rather than noise.
Ideas have life cycles just like ladies’ fashion and gentlemen’s fascination with machines. When ideas become widely adopted, they are more accurately described as fads. If you miss one, don’t worry; they be another along shortly. The publication of this book probably announces the entry of high-tech chartism into fad-dom. no doubt there will be more and more success stories reported which will generate more and more interest, and produce more and more demand for data-mining and other empirical techniques. The failures, of course, will go largely unreported. At least until one big enough occurs that is worthy of newsprint, airtime, or blog space. I am eagerly awaiting first reports.
*I am not entirely unbiased on this subject. My great uncle was Fischer Black who devised the options pricing model which is arguably a central concept of financial economics in theory and in practice.
** Simons’s mathematical background seems to make him unaware of this as a fatal flaw. Numbers, after all, have stable relationships with each other. Once discovered, these relationships never vary.
***This is not strictly true in that Goldman Sachs, for example, has an interest in keeping its proprietary pricing models confidential. However, it is essential that Goldman’s also can convince its clients that the proprietary model conforms to a responsible financial theory. The general acceptability of the theory is what matters. The rest is a matter of client faith... or gullibility.
There are essentially two ways, two visions, two philosophies, of conducting inquiry in the social sciences. In one, rational behaviour is defined by some plausible propositions; behavioural data are then analysed; and people are shown to often act irrationally. In the other philosophy, the observed patterns of human behaviour are used to define an implicit standard of rationality which may be hidden and even unconscious. These patterns (or ‘signals’) are then used to predict future states. The first is an example of the philosophy of Rationalism, which holds that laws precede and produce facts. The second is an example of Empiricism, which claims that facts precede and produce laws. The intellectual battle about which of these views is better is ancient and still hasn’t been resolved - not just in the social sciences, but also in all scientific inquiry.
Within the social sciences, financial economists are generally Rationalists. They create models of economic choice which they then use to judge the rationality (which they call efficiency) of markets, and sometimes to exploit what they find to be irrational behaviour by buying or selling to correct the situation (making the market more efficient makes money, a win/win for the individual and society, they believe). Financial chartists (or technical analysts if one prefers) are Empiricists. They look for patterns (‘structure’ in the jargon) in the movements of markets prices from which they attempt to predict future prices (chartists don’t apologise; they are in it for the money). Financial economists and chartists view each other as fools and hucksters. Economists point to the absence of chartists’ theory as proof of their irrationality. Chartists claim the lack of theory as a virtue and deride the economists ignorance of the real world. They don’t want to second-guess the market, only to understand its inherent rationality.
Historically, Rationalist financial economists had the upper hand in academic circles and among the big names in financial trading.* Beginning in the early 1950’s, its influence grew rapidly as it was taught to generations of MBA’s who spread it like an infection throughout the world. The bias toward rationalism was so pervasive that it was the primary cause of the 2007 financial crisis, which demonstrated just how irrational rationality could be. In the way of these things, fashions changed in the perennial attempt to beat the market. Empiricism was in; Rationalism was out. Old-fashioned chartism entered the realm of Artificial Intelligence and became respectable (hence the euphemism of ‘technical analysis’).
And the new chartism works. No one knows why it works. It just does, as Jimmy Simons and Robert Mercer discovered to their enormous personal benefit. Neither knows all that much about financial markets, but they know about data, raw information from a staggering array of sources, within which are hidden patterns like the traces of gold at Sutters Creek or like intelligible messages buried within the gobbledygook of an enemy code. Markets didn’t need a theory; they provide their own theory if one pays enough attention to the detail. And computer technology was just the tool that was needed to sift, sort, and correlate all the detailed data one might collect in the search for the El Dorado of financial trading.
Financial economics worked, while it worked, largely because big investors felt compelled by academic theory to act rationally. Fund managers, banks, and other fiduciaries had a duty to act rationally on behalf of their clients. In the absence of any plausible alternative, professional ethics demanded adoption of the theory. The theory, therefore, became a self-fulfilling prophecy - and the prophecies came true until the world discovered that its rationality was no more than a conventional fiction. By avoiding the intellectual arrogance of presuming it knows better than the market, the new chartists can claim to be grounded in reality not economic fantasy.
The problem of course is that no one knows why the various correlations, connections, and intersections of data work (when they do). Empiricists don’t usually look for reasons. And when they do, it is typically to rationalise the conclusions their algorithms have already produced.** The algorithms which manipulate the data may contain an implicit theory but that doesn’t really bother the Empiricist. Nor does the lack of reasons for the various correlations. Coincidence or cause, the empiricist isn’t worried. What he does worry about is someone stealing his proprietary algorithms. The Rationalist benefits by the widespread use of his theory; the Empiricist by the strict secrecy of his programmes.***
Therein lies the Empiricist’s Achilles Heel. There is literally no reason to believe his correlations are stable. There is no way to test or verify hypotheses. Technically, there are no hypotheses. And no one aside from the proprietor is checking the validity of the findings of inquiry (thus violating a fundamental principle of true scientific inquiry). Correlations may change randomly and without warning. The enemy code, if there is one, might be altered entirely from day to day. Investors who employ the chartist strategy will never know if they are, quite literally, entering uncharted territory. On the other hand, society is considerably safer in the hands of chartists, as long as they act independently of each other based on their own algorithms (something the old-fashioned chartists did not do). Some may win while others loose; but they’re unlikely to all win or lose together, thus provoking systematic misery. That, however, until enough big investors discover similar correlations and interpret them as signals rather than noise.
Ideas have life cycles just like ladies’ fashion and gentlemen’s fascination with machines. When ideas become widely adopted, they are more accurately described as fads. If you miss one, don’t worry; they be another along shortly. The publication of this book probably announces the entry of high-tech chartism into fad-dom. no doubt there will be more and more success stories reported which will generate more and more interest, and produce more and more demand for data-mining and other empirical techniques. The failures, of course, will go largely unreported. At least until one big enough occurs that is worthy of newsprint, airtime, or blog space. I am eagerly awaiting first reports.
*I am not entirely unbiased on this subject. My great uncle was Fischer Black who devised the options pricing model which is arguably a central concept of financial economics in theory and in practice.
** Simons’s mathematical background seems to make him unaware of this as a fatal flaw. Numbers, after all, have stable relationships with each other. Once discovered, these relationships never vary.
***This is not strictly true in that Goldman Sachs, for example, has an interest in keeping its proprietary pricing models confidential. However, it is essential that Goldman’s also can convince its clients that the proprietary model conforms to a responsible financial theory. The general acceptability of the theory is what matters. The rest is a matter of client faith... or gullibility.
December 14, 2021
If you, like me, have already scoured the interwebs for tidbits on Jim Simons and his Long Island quant shop, then there is not too much new stuff here in terms of the history of the company, but the story is still nice to revisit, and there are insights not presented anywhere, in particular some viewpoints from Magerman that elucidate his position and why he acted like he did. The tragic story of James Ax is also interesting, albeit unfortunately very lopsided as he wasn't around anymore to present his side, and the psychological problems underlying them are gushed over.
However, there are some weird, yet possibly not incorrect, discrepancies that seem to linger throughout the work. The most glaring is probably that Jim Simons seem to be a wholly peripheral figure in the development of RenTec; he appears occasionally in shorts and sandals wielding an ever-present Merit cigarette, but other than that it seems like he really spent most of his time running his venture capital business (which is never really explored; only very few companies are even mentioned to be related to Simons and they're all trading related, and its pretty much impossible to google anything about it) and did other things, such as the occasional math paper or founding the odd scientific laboratory - anything other than being part of building the trading business, really. Did he, for example, just show up at the office one day in the late-90s, told the employees to improve their equity trading, and then vanished into a cloud of tobacco smoke?
Another is the tough-acting Russian researcher Alexander Belopolsky that suddenly appears, is described as a bit of a problem child, apparently changes the whole atmosphere of the company, and then leaves for Izzy Englander's Millenium Capital. We, the readers, definitely missed out on the actual story which, most likely I think, included something close to a coup. A lone parenthesis mentions that people close to him disagree with the portrayal given in the book, but this is never explored, nor is the clearly significant changes he caused to the culture and development of the firm. Sure, some time is spent on poor awkward Magerman feeling a bit stressed out, but that is pretty much it.
Finally, the writing is often not very smooth, and there are numerous small mistakes in the text, such as repeated words and awkward sentences. As a more humorous example, one paragraph mentions a wife of a researcher who is a professor of speech pathology at Stony Brook, the very same paragraph ends up describing that she ends up with a PhD - in speech pathology. I'd imagine Stony Brook being a good enough university that they make people professors after they receive their PhD, not the other way around, but of course I can't be sure. The author also occasionally inserts a weird aside in a parenthesis, they most often fall flat and appear totally out of place - any decent editor would either have cut them, or at least sharpened them up.
In a sense the book is just a rehash of what everyone with a serious interest in RenTec already pretty much knew, except for a few details, but it is nice to have it all in one place and presented chronologically. However, what we already knew about RenTec, unfortunately, is pretty close to nothing - a few haphazard facts, the names of the most important people, that they run statistical arbitrage on steroids. Of course, I don't think anyone would ever have expected any book on Jim Simons or RenTec to actually tell us all about what anyone inside the vault think.
Overall, if you don't know anything about RenTec the book is probably 3.5-4 stars. If you already wasted your time digging for irrelevant trivia about the Mount Olympus of quantitative finance, then this is mostly just SparkNotes.
PS: As a relevant aside, I should point out that the Medallion returns up until 2005 are actually available, and have been for a while, in a critically under-read book (3 ratings currently on GR), Scenarios for Risk Management and Global Investment Strategies, by Rachel and Thomas Ziemba - they even include an additional significant digit (geeks rejoice!), and it all fits with the numbers Zuckerman provides, which is reassuring. The latter author was a consultant for RenTec and has some insightful views on the fund as well, plus many others and the industry, in the book. A much more recommended read than this one - unfortunately, the price appears to have shifted a bit since I picked up a used copy for around $15 shipped, the cheapest I can find is just under $1000.
However, there are some weird, yet possibly not incorrect, discrepancies that seem to linger throughout the work. The most glaring is probably that Jim Simons seem to be a wholly peripheral figure in the development of RenTec; he appears occasionally in shorts and sandals wielding an ever-present Merit cigarette, but other than that it seems like he really spent most of his time running his venture capital business (which is never really explored; only very few companies are even mentioned to be related to Simons and they're all trading related, and its pretty much impossible to google anything about it) and did other things, such as the occasional math paper or founding the odd scientific laboratory - anything other than being part of building the trading business, really. Did he, for example, just show up at the office one day in the late-90s, told the employees to improve their equity trading, and then vanished into a cloud of tobacco smoke?
Another is the tough-acting Russian researcher Alexander Belopolsky that suddenly appears, is described as a bit of a problem child, apparently changes the whole atmosphere of the company, and then leaves for Izzy Englander's Millenium Capital. We, the readers, definitely missed out on the actual story which, most likely I think, included something close to a coup. A lone parenthesis mentions that people close to him disagree with the portrayal given in the book, but this is never explored, nor is the clearly significant changes he caused to the culture and development of the firm. Sure, some time is spent on poor awkward Magerman feeling a bit stressed out, but that is pretty much it.
Finally, the writing is often not very smooth, and there are numerous small mistakes in the text, such as repeated words and awkward sentences. As a more humorous example, one paragraph mentions a wife of a researcher who is a professor of speech pathology at Stony Brook, the very same paragraph ends up describing that she ends up with a PhD - in speech pathology. I'd imagine Stony Brook being a good enough university that they make people professors after they receive their PhD, not the other way around, but of course I can't be sure. The author also occasionally inserts a weird aside in a parenthesis, they most often fall flat and appear totally out of place - any decent editor would either have cut them, or at least sharpened them up.
In a sense the book is just a rehash of what everyone with a serious interest in RenTec already pretty much knew, except for a few details, but it is nice to have it all in one place and presented chronologically. However, what we already knew about RenTec, unfortunately, is pretty close to nothing - a few haphazard facts, the names of the most important people, that they run statistical arbitrage on steroids. Of course, I don't think anyone would ever have expected any book on Jim Simons or RenTec to actually tell us all about what anyone inside the vault think.
Overall, if you don't know anything about RenTec the book is probably 3.5-4 stars. If you already wasted your time digging for irrelevant trivia about the Mount Olympus of quantitative finance, then this is mostly just SparkNotes.
PS: As a relevant aside, I should point out that the Medallion returns up until 2005 are actually available, and have been for a while, in a critically under-read book (3 ratings currently on GR), Scenarios for Risk Management and Global Investment Strategies, by Rachel and Thomas Ziemba - they even include an additional significant digit (geeks rejoice!), and it all fits with the numbers Zuckerman provides, which is reassuring. The latter author was a consultant for RenTec and has some insightful views on the fund as well, plus many others and the industry, in the book. A much more recommended read than this one - unfortunately, the price appears to have shifted a bit since I picked up a used copy for around $15 shipped, the cheapest I can find is just under $1000.
This entire review has been hidden because of spoilers.
December 29, 2020
Every few months, I get a LinkedIn message from a headhunter regarding a discreet search by a secretive firm in the New York area. The message will reference a team of leading computer scientists and mathematicians. Some will use adjectives like "renowned" and "legendary" and phrases like "total compensation in excess of $500k."
My trader friends and I, a technologist with no academic credentials aside from being the first person at my college to turn a B+ into a teaching assistant role for a C++ class, always hope it is RenTec. However, we stopped responding to the messages once we realized that they were written so as to fool us into thinking the firm was RenTec, which Jim Simons founded and is the subject of this book. Not to say that any of the other companies fitting the descriptions aren't impressive or that I don't want to make $500k+, it's just that there is special prestige afforded to the place.
The book is well-written in a style you'd expect from the Journal. The author pays homage to many significant points in the history of quantitative trading while providing a clear idea of Renaissance Technologies' place in it all. It's easy to lose sight of the likelihood of this book never having been written at all. But here we are.
I did not find the read particularly rewarding or worth skipping my morning run for. Particularly distasteful was the attitude toward Bob Mercer's role in helping Donald Trump get elected. I get it, you can't ignore that Mercer, co-CEO of RenTec, was instrumental in getting Trump elected. I didn't know this! But there is snark insinuating Trump == Bad for more pages than I'd care to read on a Sunday morning and cancel culture assured the guy had to step down from his role at RenTec anyway.
I also took issue with the implication that Thomas Sowell, who is black (omitted), wrote economic and social theory books that were being used to further agendas of white supremacy. I read one of his lesser-known books, Race and Economics, and referenced it for a final paper in a class about slavery and got an A. But that was over three years ago. It's unfortunate that public discourse, especially that being directed by my dear WSJ, doesn't allow this type of thing to be discussed in a healthy way.
Anyway, the most common criticism is going to be that it isn't clear at all what innovations were actually made through the 2000s and that Jim himself took a largely managerial role early on. Much of the book is about the supporting cast, who thankfully were all weirdos. I was still kind of pissed about the Trump stuff but the end of the book is prescient regarding the current state of the industry and the current angles data people at trading firms are exploring. It's a must-read because it's RenTec (and because it highlights a quote from Gary Shteyngart who wrote the satirical book Lake Success, my favorite of 2018) but if this can't be it, I doubt we'll ever get the modern-day trading classic we've been waiting for.
My trader friends and I, a technologist with no academic credentials aside from being the first person at my college to turn a B+ into a teaching assistant role for a C++ class, always hope it is RenTec. However, we stopped responding to the messages once we realized that they were written so as to fool us into thinking the firm was RenTec, which Jim Simons founded and is the subject of this book. Not to say that any of the other companies fitting the descriptions aren't impressive or that I don't want to make $500k+, it's just that there is special prestige afforded to the place.
The book is well-written in a style you'd expect from the Journal. The author pays homage to many significant points in the history of quantitative trading while providing a clear idea of Renaissance Technologies' place in it all. It's easy to lose sight of the likelihood of this book never having been written at all. But here we are.
I did not find the read particularly rewarding or worth skipping my morning run for. Particularly distasteful was the attitude toward Bob Mercer's role in helping Donald Trump get elected. I get it, you can't ignore that Mercer, co-CEO of RenTec, was instrumental in getting Trump elected. I didn't know this! But there is snark insinuating Trump == Bad for more pages than I'd care to read on a Sunday morning and cancel culture assured the guy had to step down from his role at RenTec anyway.
I also took issue with the implication that Thomas Sowell, who is black (omitted), wrote economic and social theory books that were being used to further agendas of white supremacy. I read one of his lesser-known books, Race and Economics, and referenced it for a final paper in a class about slavery and got an A. But that was over three years ago. It's unfortunate that public discourse, especially that being directed by my dear WSJ, doesn't allow this type of thing to be discussed in a healthy way.
Anyway, the most common criticism is going to be that it isn't clear at all what innovations were actually made through the 2000s and that Jim himself took a largely managerial role early on. Much of the book is about the supporting cast, who thankfully were all weirdos. I was still kind of pissed about the Trump stuff but the end of the book is prescient regarding the current state of the industry and the current angles data people at trading firms are exploring. It's a must-read because it's RenTec (and because it highlights a quote from Gary Shteyngart who wrote the satirical book Lake Success, my favorite of 2018) but if this can't be it, I doubt we'll ever get the modern-day trading classic we've been waiting for.
February 11, 2020
It's not a bad book. If you like biographies focused on year by year events you will enjoy it.
I was expecting something else. Some market knowledge, some mathematical formulas.
The whole book is like listening to grandpa's story, where he is talking about himself, missing on every interesting fact and plot.
Also, in the end, we get into politics, making this even worse.
I was expecting something else. Some market knowledge, some mathematical formulas.
The whole book is like listening to grandpa's story, where he is talking about himself, missing on every interesting fact and plot.
Also, in the end, we get into politics, making this even worse.
Want to read
November 14, 2019I've always wondered what Jim Simons, the liberal leaning head of Renaissance Technologies, thought of the co-head of his firm, Robert Mercer. I hope Simons lives long enough to see the consequences of helping Mercer to his billions.
This book, reviewed in the NYT - How to Beat the Market, may provide some insight, to quote:
This book, reviewed in the NYT - How to Beat the Market, may provide some insight, to quote:
You can certainly argue, as one former Renaissance executive does, that hedge funds are “a game in which rich people play around with each other, and it doesn’t do the world much good.” You could also argue, as another former executive guiltily put it, that working for Renaissance “helped provide Mercer with the resources to put Trump in office.”The interview I recall Simons once did with vice.com seems to have been taken down and I regret not keeping a copy. FT article here as well: The Man Who Solved the Market — how Jim Simons built a moneymaking machine
August 19, 2020
Very disappointing. I read it in 10 hours or so, at least 8 were a waste of time.
The title is surely chosen by the publisher as a marketing gimmick. It's not *that* much about Jim Simons, in fact past certain years (the 80s?) it's about Brown and Mercer, who came from IBM where they did natural language processing.
Basically the algorithm needs to "understand" what you're saying by trying to guess what are you *going* to say:
e.g. if you say "apple" the algo will apply a high probablity that the following word will be "pie", under specific circumstances.
So, one "principle" behind the modus operandi of some algorithms employed by RenTech is this one.
It doesn't dig deep into the math, the importance of discoveries by Simons and his PhD friends.
The author seems concerned with how much tall the guys are, what food did they brought to work, the brand of the cigarettes smoked by Simons, how much money did they play in poker, the back story about the sons and daughters of the employees.
Very little is said about the guys who stole the code and brought elsewhere.
There's an introduction of a non-collaborative new hire who raises near the top, some old guys aren't happy with his lacking team-play, he said the bad mouthed Mercer and Brown and the same Brown wants to keep him because he adds value. In the same chapter he introduces the two that stole the code
(but the theft happened earlier, and then on the following chapter he vaguely explain what happened to the two thieves, but not much is said about how they came to the fund, how they left, etc... - at least, I hope I didn't get distracted - ).
There's one or one and a half chapter talking about Mercer and his political donations and about the election. Who gives a fu**. From 2008 he went to one episode of 2010 (market flash crash?) to another one where Jim didn't believe the algos and wanted to painc sell in '12(?) and then straight to Mercer's political exploits in '15-16-18.
The author constantly talks about how bad things were going in basically every year, it makes the company (because really early in the book Simons seems to not be the relevant person running the operations that make money to the company) look like they were always on the verge of going badly, while the hard data that he himself provides show the other way.
He wants to led us to think that they struggled or that they did badly because minor episode costed millions on a tuesday (or whatever), then you go check and the fund was up 20 or 30% for the year, and the least paid employee probably took a 7 figures salary.
I understand why he needs to be overly dramatic, but it pi**es me off.
Overall, that's exactly the book I expected about someone/some entity covered with lifetime NDAs by anyone: mostly fluff/useless trivia
Skip it, don't fall for the peer pressure to having to read it because someone said he did it as well.
The title is surely chosen by the publisher as a marketing gimmick. It's not *that* much about Jim Simons, in fact past certain years (the 80s?) it's about Brown and Mercer, who came from IBM where they did natural language processing.
Basically the algorithm needs to "understand" what you're saying by trying to guess what are you *going* to say:
e.g. if you say "apple" the algo will apply a high probablity that the following word will be "pie", under specific circumstances.
So, one "principle" behind the modus operandi of some algorithms employed by RenTech is this one.
It doesn't dig deep into the math, the importance of discoveries by Simons and his PhD friends.
The author seems concerned with how much tall the guys are, what food did they brought to work, the brand of the cigarettes smoked by Simons, how much money did they play in poker, the back story about the sons and daughters of the employees.
Very little is said about the guys who stole the code and brought elsewhere.
There's an introduction of a non-collaborative new hire who raises near the top, some old guys aren't happy with his lacking team-play, he said the bad mouthed Mercer and Brown and the same Brown wants to keep him because he adds value. In the same chapter he introduces the two that stole the code
(but the theft happened earlier, and then on the following chapter he vaguely explain what happened to the two thieves, but not much is said about how they came to the fund, how they left, etc... - at least, I hope I didn't get distracted - ).
There's one or one and a half chapter talking about Mercer and his political donations and about the election. Who gives a fu**. From 2008 he went to one episode of 2010 (market flash crash?) to another one where Jim didn't believe the algos and wanted to painc sell in '12(?) and then straight to Mercer's political exploits in '15-16-18.
The author constantly talks about how bad things were going in basically every year, it makes the company (because really early in the book Simons seems to not be the relevant person running the operations that make money to the company) look like they were always on the verge of going badly, while the hard data that he himself provides show the other way.
He wants to led us to think that they struggled or that they did badly because minor episode costed millions on a tuesday (or whatever), then you go check and the fund was up 20 or 30% for the year, and the least paid employee probably took a 7 figures salary.
I understand why he needs to be overly dramatic, but it pi**es me off.
Overall, that's exactly the book I expected about someone/some entity covered with lifetime NDAs by anyone: mostly fluff/useless trivia
Skip it, don't fall for the peer pressure to having to read it because someone said he did it as well.
February 22, 2023
چگونه یک هندسهدان ثروتی 23 میلیارد دلاری بههم زد
اشکال کتاب این است که خیلی کم به فعالیتهای خیرخواهانهی سایمنز پرداخته. بهترین نمود این فعالیتها موسسهی سایمنز است که از بزرگترین نهادهای خصوصی حامی پروژههای علمی در دنیا و مهمترینشان است
اشکال کتاب این است که خیلی کم به فعالیتهای خیرخواهانهی سایمنز پرداخته. بهترین نمود این فعالیتها موسسهی سایمنز است که از بزرگترین نهادهای خصوصی حامی پروژههای علمی در دنیا و مهمترینشان است
June 22, 2020
I thoroughly enjoyed this book. It was exactly what I was looking forward to reading- the growth of quant-based trading in finance through the lens of arguably the most successful firm in the field.
It's important to note what this book is NOT about. Firstly, it certainly doesn't just trace the life of Jim Simons- only about 25% of the book is about him. This book is about The *Men* Who Solved the Market and about the people who make/made RenTech. Secondly, it's definitely not about trading strategies and doesn't talk about any "quant"/math that you wouldn't know already.
It's a book about mathematicians, about scientists, about their decisions, passions and motivations - and how a few unrelenting men with great intelligence came up with a good idea and worked on it for decades to create a new field, whose by-product was large sums of money.
It seems impossible to me that anyone who is purely motivated by money could pull this off, which is what I really enjoyed about these personalities who made RenTech. (Even though its eluded to many times in the book that Simons was business minded, which was supposed to reassure the reader that Simon's priority was just making money- his actions and decisions just didn't match up to that).
I really didn't care for the politics in the ending. Having to read about what Jim/Mercer did/supported politically honestly was probably the reason why I'm giving this book 4 stars and not 5. Another reason would be that I really wanted to know more- not just about the people but also their professional challenges and their ideas. I'll have to go look for that in another book(if such a book exists) but I'm satisfied with this read for now!
It's important to note what this book is NOT about. Firstly, it certainly doesn't just trace the life of Jim Simons- only about 25% of the book is about him. This book is about The *Men* Who Solved the Market and about the people who make/made RenTech. Secondly, it's definitely not about trading strategies and doesn't talk about any "quant"/math that you wouldn't know already.
It's a book about mathematicians, about scientists, about their decisions, passions and motivations - and how a few unrelenting men with great intelligence came up with a good idea and worked on it for decades to create a new field, whose by-product was large sums of money.
It seems impossible to me that anyone who is purely motivated by money could pull this off, which is what I really enjoyed about these personalities who made RenTech. (Even though its eluded to many times in the book that Simons was business minded, which was supposed to reassure the reader that Simon's priority was just making money- his actions and decisions just didn't match up to that).
I really didn't care for the politics in the ending. Having to read about what Jim/Mercer did/supported politically honestly was probably the reason why I'm giving this book 4 stars and not 5. Another reason would be that I really wanted to know more- not just about the people but also their professional challenges and their ideas. I'll have to go look for that in another book(if such a book exists) but I'm satisfied with this read for now!
August 7, 2020
I had always believed in the efficient market hypothesis. This book convinced me that I was wrong: it's not that there aren't inefficiencies to be exploited in financial markets, it's just that humans suck at seeing them. The same cognitive biases that create those inefficiencies in the first place also prevent us from exploiting them. We see signal where there is only noise, we anchor our expectations, we become emotionally invested in our choices. But the machine is immune to all that.
Zuckerman gets into a lot more detail about Renaissance's models than I expected him to. I guess by now there are enough ex-employees willing to share company secrets. Or maybe the company secrets they are willing to share are not that big anymore: using Markov chains to model price movements, looking for price ratios instead of absolute prices, etc. Whatever is happening at quant funds right now is probably way beyond any of that (convolutional neural networks that count cars in Walmart's parking lots, that sort of thing).
I was ready to roll up my sleeves and start modelling stuff, but fortunately I got to this point in the book first: "In the five years leading up to spring of 2019, quant-focused hedge funds gained about 4.2 percent a year on average, compared with a gain of 3.3 percent for the average hedge fund in the same period." Well, the S&P500 yields on average 9.8% a year (6% after inflation). For Simons to get his average 66% yearly return he had to hire a team of geniuses. I'm no genius, and I'm not in a position to hire any geniuses to work for me, so I guess I'm staying with index funds (except maybe for some "fun money").
Overall this is a well written, well researched book, and I got a lot out of it.
Zuckerman gets into a lot more detail about Renaissance's models than I expected him to. I guess by now there are enough ex-employees willing to share company secrets. Or maybe the company secrets they are willing to share are not that big anymore: using Markov chains to model price movements, looking for price ratios instead of absolute prices, etc. Whatever is happening at quant funds right now is probably way beyond any of that (convolutional neural networks that count cars in Walmart's parking lots, that sort of thing).
I was ready to roll up my sleeves and start modelling stuff, but fortunately I got to this point in the book first: "In the five years leading up to spring of 2019, quant-focused hedge funds gained about 4.2 percent a year on average, compared with a gain of 3.3 percent for the average hedge fund in the same period." Well, the S&P500 yields on average 9.8% a year (6% after inflation). For Simons to get his average 66% yearly return he had to hire a team of geniuses. I'm no genius, and I'm not in a position to hire any geniuses to work for me, so I guess I'm staying with index funds (except maybe for some "fun money").
Overall this is a well written, well researched book, and I got a lot out of it.
March 13, 2020
Zuckerman is a superb spinner of complex stories, his latest book is no exception. Quantitative investing developed over the last 40 years as a result of increased use of mathematical formulas and large data sets. The theory assumed that the new methods would eliminate human errors.
The book concentrates on James Simons who began life as a distinguished mathematician and evolved into a very successful investment firm. The results of building these new models was phenomenal.
But Zuckerman also does a great job of explaining that even with taking out the human errors in investing does not eliminate the human conflict in firms. As the firm developed the egos of the math professionals did not stop rivalries.
Where I would fault the book when he gets into the politics of one of the key players and the tax policies of how to treat the kinds of hedge investments that are critical to the Simons style of investing. Robert Mercer, who became co-CEO of Renaissance Technologies when Simons retired became controversial because of his beliefs on a limited government and the effects of various policies including the Civil Rights Act of 1964. He was also a key funder of the Trump 2016 campaign (after Ted Cruz dropped out) and of the move in the UK for Brexit. But Zuckerman's descriptions of his actions lack nuance. I would have also liked a bit more discussion of the errors of Long Term Capital Management - which was another quant approach which failed horribly.
There is one other issue which some of the reviewers raise - Simons assumption is that there are patterns in markets which can be discovered. And his firm has spent several decades continuing to refine their models based on the increasing availability of data. The problem with the basic theory is that the patterns may be more apparent than real; some market behavior may be genuinely irrational - take a look at the last ten days of market performance at the time this review is being written. Warren Buffet's notion of Mr. Market (the irrational guy who decides market direction) may actually be truer than Simons and other rationalists would believe.
Even with those limits this book is a good discussion of how quant theory developed and who some of the major players in developing the theory were.
The book concentrates on James Simons who began life as a distinguished mathematician and evolved into a very successful investment firm. The results of building these new models was phenomenal.
But Zuckerman also does a great job of explaining that even with taking out the human errors in investing does not eliminate the human conflict in firms. As the firm developed the egos of the math professionals did not stop rivalries.
Where I would fault the book when he gets into the politics of one of the key players and the tax policies of how to treat the kinds of hedge investments that are critical to the Simons style of investing. Robert Mercer, who became co-CEO of Renaissance Technologies when Simons retired became controversial because of his beliefs on a limited government and the effects of various policies including the Civil Rights Act of 1964. He was also a key funder of the Trump 2016 campaign (after Ted Cruz dropped out) and of the move in the UK for Brexit. But Zuckerman's descriptions of his actions lack nuance. I would have also liked a bit more discussion of the errors of Long Term Capital Management - which was another quant approach which failed horribly.
There is one other issue which some of the reviewers raise - Simons assumption is that there are patterns in markets which can be discovered. And his firm has spent several decades continuing to refine their models based on the increasing availability of data. The problem with the basic theory is that the patterns may be more apparent than real; some market behavior may be genuinely irrational - take a look at the last ten days of market performance at the time this review is being written. Warren Buffet's notion of Mr. Market (the irrational guy who decides market direction) may actually be truer than Simons and other rationalists would believe.
Even with those limits this book is a good discussion of how quant theory developed and who some of the major players in developing the theory were.
November 6, 2019
An Excellent Biography, I enjoyed reading political factions within a company. It seems that it can be applied everywhere.
I would recommend this to people who are interested in Biographies, Investment, Wall-Street.
Deus Vult,
Gottfried
I would recommend this to people who are interested in Biographies, Investment, Wall-Street.
Deus Vult,
Gottfried
November 10, 2019
A nice telling of the people behind Renaissance Technologies, although I would've liked more math and equations
November 29, 2019
The story of the genius who is able to make huge profits through some foolproof formula or algorithm--except when he is wrong--is now so common that it feels like I've read this one before.
November 26, 2019
My college roommate’s brother was completing his PhD and called me to ask what I thought of the offer he had to join Renaissance. I advised him that they were in all probability a fraud and he should get a real job at a real Wall St. company. Thank goodness he did not take my advice. He’s done OK, and so have they, of course.
Ordered the book without asking him what he thought of it. Glad I did, if you’re from my business you’ll probably enjoy it a lot. It was a relief to read an employee also thought they were probably a fraud, only to sit down and audit the numbers and realize they are actually 100% genuine.
I did not buy this to find out who worked with Simons and what their background was and how they got on with each other and with their wives; and, if I’m honest, the names are so many and their quirks so mundane, that I lost track. A “cast of characters” page somewhere up front would probably have been helpful. And all the business about Mercer and Bannon I could have done without, it hardly belongs.
No, I bought this to found out how they did it.
Turns out they rode the market up: their returns have been stellar forever, but prior to 2003 it was on the kind of money on which you can do RV. Since then it’s been on the kind of money where you need to be long outright, and that’s what they seem to have done, or else they would not have suffered sleepless nights on the rare occasions when they did. I lived those days myself, I know what I’m talking about.
But they rode this bull market better than anybody else and in bigger size than anybody else, so kudos to them, well done!
As for the book, if it had not answered that burning question of mine, I don’t think it would have been of enormous interest, I’m not too deeply into the private lives and habits of miserly billionaires who bring packed lunch to work. That is not to take anything away from the book, however, and the speed at which I read it indicates I probably liked it plenty more than I care to admit.
Ordered the book without asking him what he thought of it. Glad I did, if you’re from my business you’ll probably enjoy it a lot. It was a relief to read an employee also thought they were probably a fraud, only to sit down and audit the numbers and realize they are actually 100% genuine.
I did not buy this to find out who worked with Simons and what their background was and how they got on with each other and with their wives; and, if I’m honest, the names are so many and their quirks so mundane, that I lost track. A “cast of characters” page somewhere up front would probably have been helpful. And all the business about Mercer and Bannon I could have done without, it hardly belongs.
No, I bought this to found out how they did it.
Turns out they rode the market up: their returns have been stellar forever, but prior to 2003 it was on the kind of money on which you can do RV. Since then it’s been on the kind of money where you need to be long outright, and that’s what they seem to have done, or else they would not have suffered sleepless nights on the rare occasions when they did. I lived those days myself, I know what I’m talking about.
But they rode this bull market better than anybody else and in bigger size than anybody else, so kudos to them, well done!
As for the book, if it had not answered that burning question of mine, I don’t think it would have been of enormous interest, I’m not too deeply into the private lives and habits of miserly billionaires who bring packed lunch to work. That is not to take anything away from the book, however, and the speed at which I read it indicates I probably liked it plenty more than I care to admit.
December 16, 2019
Show me the money! Prove it, in other words, a major mantra in my financial services world and prove it they do. Renaissance Technology, despite the highest fees among major hedge funds has managed to return, net, over 39% per year after fees since 1988. How, you might ask, as you dive into this book to discover the secret. Yeah, good luck with that! With all the non-disclosure agreements in place you aren't likely to find out. The author has done a good job taking some bare facts and critical details and weaving a narrative around them. Basic thrust is that Simon, a mathematician hired other accomplished mathematicians to determine patterns that could predict stock market returns. Interestingly, despite the rapid trading, sophisticated models and wealthy drivers, the system he developed is right only 51% of the time. But that is all it takes to produce billionaires by the bushel. Some interesting side trips on the political side as Simon became a supporter of liberal causes and his partner Mercer virtually put Trump in office. So, as much for the general interest market as it is for professionals. No need to fear any math, those details tend to not be available beyond returns and assets under management and the discussion of IRS battles. (They used bank contracts to convert ordinary income into capital gains at much lower rates. IRS lost that battle, not sure why.) Anyway, well written by an experienced financial journalist so gets the 4 star rating.
November 13, 2019
It's amazing to think that the biggest/baddest hedge fund of all time was not founded by Wall Street types but a math professor from MIT/Stony Brook who relentlessly pursued wealth, and assembled a team of math wizards and computer scientists from Cornell, Stony Brook and IBM.
From the book, it sounds like many of the models were Hidden Markov Models, and stochastic differential equations - which I never got to in my schooling, but maybe one day if I have the chance and discipline?
One guy Strauss spent his efforts gathering and cleaning data - and it was amazing that for a long time people only used the opening and closing prices as the data points for their models, until Strauss obtained the TIC data (or much more granular trading price/volume data). As a data engineer myself, I can relate to both the tedium as well as the pride one gets in wrangling messy data to make it usable for others.
I've read Zuckerman's earlier work The Greatest Trade ever on Paulson and Pellegrini's short of the housing bubble, which was great - and I'm considering picking up his book on the fracker oil barons.
From the book, it sounds like many of the models were Hidden Markov Models, and stochastic differential equations - which I never got to in my schooling, but maybe one day if I have the chance and discipline?
One guy Strauss spent his efforts gathering and cleaning data - and it was amazing that for a long time people only used the opening and closing prices as the data points for their models, until Strauss obtained the TIC data (or much more granular trading price/volume data). As a data engineer myself, I can relate to both the tedium as well as the pride one gets in wrangling messy data to make it usable for others.
I've read Zuckerman's earlier work The Greatest Trade ever on Paulson and Pellegrini's short of the housing bubble, which was great - and I'm considering picking up his book on the fracker oil barons.
November 16, 2019
A story about numbers, markets, causes, money and ultimately humanity
Given the secrecy of Renaissance Technologies, this must have been a very difficult book to research and write, and shines light on a most successful investment firm, if not the most successful. What Zuckerman achieved however is to both explain how Renaissance went about creating its algorithms and training systems, but also the motivations and lives of the characters in the story.
[Spoiler alert]
What is fascinating however is the impact of money on the characters. How life kept happening with both random tragedies and own goals. How people grate each other in spite of having no material shortcomings. Regardless of how smart people are mathematically, it does not impart wisdom or even just kindness.
It is a challenging book. Challenging in that it questions pursuits. It is hard to argue that Renaissance Technologies has any social purpose, other than to make its employees rich. It must be highly frustrating for a bulk of the team that their monetary successes contributed to history changing events such as Trump and Brexit.
A book worth reading.
Given the secrecy of Renaissance Technologies, this must have been a very difficult book to research and write, and shines light on a most successful investment firm, if not the most successful. What Zuckerman achieved however is to both explain how Renaissance went about creating its algorithms and training systems, but also the motivations and lives of the characters in the story.
[Spoiler alert]
What is fascinating however is the impact of money on the characters. How life kept happening with both random tragedies and own goals. How people grate each other in spite of having no material shortcomings. Regardless of how smart people are mathematically, it does not impart wisdom or even just kindness.
It is a challenging book. Challenging in that it questions pursuits. It is hard to argue that Renaissance Technologies has any social purpose, other than to make its employees rich. It must be highly frustrating for a bulk of the team that their monetary successes contributed to history changing events such as Trump and Brexit.
A book worth reading.
July 24, 2020
Entertaining book, very enjoyable as an audio-book. More about the people behind Renaissance, the best performing hedge fund of all time, than the technology itself. One of the more scary stories is about Robert Mercer, former co-CEO of renaissance, who had a huge role in funding Trump's presidency with the billions he's made through Renaissance.
Overall, probably not a story I'll see myself refer back to as much as I hoped, but Zuckerman put himself in a tough position trying to dig up information on one of the most secretive companies on earth.
Overall, probably not a story I'll see myself refer back to as much as I hoped, but Zuckerman put himself in a tough position trying to dig up information on one of the most secretive companies on earth.
March 9, 2023
A really interesting story about a wall street firm that would create spectacular levels of wealth but did not contain anyone from wall street. This is the irony of the success of the firm, the firm held only mathematicians and computer scientists. Many who had no clue about the business their algorithms invested in or shares they held or sold. Simons pioneered the computer model revolution on wall street. Looking for patterns based on investor behavior rather than solely focusing on stocks or trades that scoured for inefficiencies. Using sophisticated algorithms with techniques such as machine learning models that were unheard of at the time. Simons started doing these models in the 70's perhaps in the 60's. Decades before they would become universal and apart of our everyday lives. Which is why he is worth over 20 billion at the time of this writing.
Isn't is odd how on wall street, you can create nothing of value and still generate enormous wealth? At least with tech billionaires they provided a service but the wall street billionaires do not create anything but rather extract from markets. It's almost another universe there detached from the physical world. I think it will be an issue in the coming years, how a system is designed for enormous wealth to be created that has nothing to do with the economy as a whole. Algorithms, rampant speculation on commodities that ballon the prices globally. At one point in the story, the algorithm for Simons firm blew up the wheat market sending shares soaring, think about how that impacts our wallets globally? The speculation influences prices globally over bets that have nothing to do with the commodity itself? What a bizarre system.
Why did I rate this 2 stars? This book could probably be cut 100 pages, there is a large portion of the book filled with corporate gossip, co workers tell disparaging stories about one another that brings no value to the story. It's up to the author to decide what is noise and what is the signal and in that since he failed. However, some pieces of corporate battles were interesting, this isn't gossip but inter political battles. The level of infighting that took place within such a successful company is perplexing, these people are fucking millionaires and fighting to throw one another under the bus for an extra percentage point. Often getting in arguments over silly topics, it goes to show you even with spectacular wealth, it does not bring a level of wisdom and understanding. Many in the firm were angry at others who got paid a little bit more because they thought they worked harder. These are people making 8 figures a year, playing with numbers and still getting upset over the smallest perceived slight. That might be the most interesting part, groups of humans where money and power flow.... Gets real messy and unbearable.
If you're heavily into wall street, maybe pick this up. The gossip stories are so weird that it misses the bigger picture. Over 25% of the book is filled with these little annoying stories "He said this and then she said this and then another person said this". My friend, why do I give a shit about any of this? Its almost like the author has a page quota to reach and he was simply extending the story to meet that requirement. It almost reminded me of how I use to bullshit word count essay's by just rambling on and on without saying anything.
2 stars.
Isn't is odd how on wall street, you can create nothing of value and still generate enormous wealth? At least with tech billionaires they provided a service but the wall street billionaires do not create anything but rather extract from markets. It's almost another universe there detached from the physical world. I think it will be an issue in the coming years, how a system is designed for enormous wealth to be created that has nothing to do with the economy as a whole. Algorithms, rampant speculation on commodities that ballon the prices globally. At one point in the story, the algorithm for Simons firm blew up the wheat market sending shares soaring, think about how that impacts our wallets globally? The speculation influences prices globally over bets that have nothing to do with the commodity itself? What a bizarre system.
Why did I rate this 2 stars? This book could probably be cut 100 pages, there is a large portion of the book filled with corporate gossip, co workers tell disparaging stories about one another that brings no value to the story. It's up to the author to decide what is noise and what is the signal and in that since he failed. However, some pieces of corporate battles were interesting, this isn't gossip but inter political battles. The level of infighting that took place within such a successful company is perplexing, these people are fucking millionaires and fighting to throw one another under the bus for an extra percentage point. Often getting in arguments over silly topics, it goes to show you even with spectacular wealth, it does not bring a level of wisdom and understanding. Many in the firm were angry at others who got paid a little bit more because they thought they worked harder. These are people making 8 figures a year, playing with numbers and still getting upset over the smallest perceived slight. That might be the most interesting part, groups of humans where money and power flow.... Gets real messy and unbearable.
If you're heavily into wall street, maybe pick this up. The gossip stories are so weird that it misses the bigger picture. Over 25% of the book is filled with these little annoying stories "He said this and then she said this and then another person said this". My friend, why do I give a shit about any of this? Its almost like the author has a page quota to reach and he was simply extending the story to meet that requirement. It almost reminded me of how I use to bullshit word count essay's by just rambling on and on without saying anything.
2 stars.
July 10, 2020
I’m a bit of a nerd for a well written book on finance - think Michael Lewis.
And this is a winner.
Putting aside strong readability, what the author puts across or what conclusions I draw are that the markets are a mechanism.
Looking at companies or sectors is irrelevant. Renaissance enjoyed huge returns by simply sifting Big Data. Humans are irrelevant. The companies they command are mere replaceable cogs in a language of financial numbers.
More so, that these data analyzers fare well whether the market goes up or down and one gets an almost Alice in Wonderland feeling.
The day the markets go to zero will be the day Simmons firm will have its best day of profits, the Red Queen intoned.
Finally and surprisingly is the Trump effect that seeps into an area that one would think would be immune, but even here one has partners being pressured for their heterodox political support, accusations of racism, and dumbfounded musings over how someone so smart could support Trump.
And this is a winner.
Putting aside strong readability, what the author puts across or what conclusions I draw are that the markets are a mechanism.
Looking at companies or sectors is irrelevant. Renaissance enjoyed huge returns by simply sifting Big Data. Humans are irrelevant. The companies they command are mere replaceable cogs in a language of financial numbers.
More so, that these data analyzers fare well whether the market goes up or down and one gets an almost Alice in Wonderland feeling.
The day the markets go to zero will be the day Simmons firm will have its best day of profits, the Red Queen intoned.
Finally and surprisingly is the Trump effect that seeps into an area that one would think would be immune, but even here one has partners being pressured for their heterodox political support, accusations of racism, and dumbfounded musings over how someone so smart could support Trump.
November 25, 2019
Fairly shallow overview of the Renaissance hedge fund company, especially on founder Jim Simons. There are a few obvious inaccuracies, but it seems to get the big picture right. The book is fairly balanced: on the one hand the company has made a few billionaires and given some NYC math teachers $15K bonuses, while on the other hand it has boosted white supremacy, supported climate denialism and been key to Trump's election. I was surprised to learn how little competition the firm faced at least initially, just DE Shaw and LTCM; it really is a small world.
June 8, 2023
More a story of *men* who solved the market, than just Jim Simons himself, whose role at RenTech seemed more hands-off than I'd previously assumed. Respectable journalism at work here, tracking down the little that could be pieced together about the secretive firm. Zuckerman seems to have traced the most significant events in the firm's history and its leading players, but there's only so much technical history he can figure out. Alludes to some interesting tensions, sociological and otherwise, between quants vs trad investors (for lack of a better word) before the former (I think?) reigned supreme. Was hoping for more details re: the persistence of their competitive advantages, which were explored several times but never comprehensively. The political tension between RenTech founder Simons, a top Dem donor, and CEO Mercer, possibly Trump/Brexit's biggest backer, only feature in a chapter towards the end about the 2016 election, despite them working together for 20+ years before that. I guess that's wealth and its pursuit insulating them otherwise.
December 3, 2019
Greg Zuckerman has done a great job giving readers a peak inside the secretive world of Jim Simons and Renaissance Technologies hedge fund operations.
Jim Simons Renaissance Technologies has been the greatest money making operation in the modern financial markets. No other investor or fund has had better returns over as long a time period, not Warren Buffett, Paul Tudor Jones, Peter Lynch, Ray Dalio, or George Soros. No one is in the same league of his fund’s lifetime returns on an annual and compounded basis.
Renaissance’s flagship Medallion fund has returned an average annual gain of 66% since 1988. His hedge fund has earned profits of over $100 billion. Jim Simons personal net worth is $23 billion dollars.
Jim Simons went from being a mathematics professor with a PhD. who operated a successful math department in a university to focusing on solving the patterns in the financial markets for profits.
Jim Simons belief system started with: “There are patterns in the market, I know we can find them.” With this foundation he hired some of the best mathematicians, statisticians, computer programmers, and scientists to find them. He was successful, he found them.
His fund started out with a successful futures trading system and branched off into other markets including bonds, currencies, and the stock market.
Renaissance was one of the first quantitative hedge funds that compiled a huge data base of end of day and intra-day price action history of financial markets and ran powerful computer backtests on the historical data to find market patterns of correlations and repeating price moves in short time frames based on relationships between catalysts and investors behavior.
His fund reduced the financial markets to a math problem and ignored the fundamentals and focuses on the way prices move. Renaissance makes thousands of trades a day on short time frames from hours to days and makes money on a little over 50% of their trades but their winners are bigger than their losers and the edge creates windfall profits on an astounding risk adjusted basis.
His money making fund is very similar to a casino exercising his mathematical edge over and over with small bets in relation to his total capital. The fund does use leverage but it is for trading in smaller diversified trades in volume not making large bets on any one trade in size.
Jim Simons was a master administrator in hiring the right people for his fund and leading them in the right direction for developing robust trading systems using scientific methods. One of the biggest edges his quant fund had was being one of the first to the market using his method, he had one of the most thorough historical price action data bases, and he removed the human weaknesses of emotions and ego out of his trading method.
If you love math and you love trading you will enjoy this book as it takes a deep dive into both. It is an easy and enjoyable read and is written more like a novel than a trading book.
I have read several hundred trading and investing books and I would put this one on my list of the top five trading books every written. This is a unique look into how quantitative trading works.
Jim Simons Renaissance Technologies has been the greatest money making operation in the modern financial markets. No other investor or fund has had better returns over as long a time period, not Warren Buffett, Paul Tudor Jones, Peter Lynch, Ray Dalio, or George Soros. No one is in the same league of his fund’s lifetime returns on an annual and compounded basis.
Renaissance’s flagship Medallion fund has returned an average annual gain of 66% since 1988. His hedge fund has earned profits of over $100 billion. Jim Simons personal net worth is $23 billion dollars.
Jim Simons went from being a mathematics professor with a PhD. who operated a successful math department in a university to focusing on solving the patterns in the financial markets for profits.
Jim Simons belief system started with: “There are patterns in the market, I know we can find them.” With this foundation he hired some of the best mathematicians, statisticians, computer programmers, and scientists to find them. He was successful, he found them.
His fund started out with a successful futures trading system and branched off into other markets including bonds, currencies, and the stock market.
Renaissance was one of the first quantitative hedge funds that compiled a huge data base of end of day and intra-day price action history of financial markets and ran powerful computer backtests on the historical data to find market patterns of correlations and repeating price moves in short time frames based on relationships between catalysts and investors behavior.
His fund reduced the financial markets to a math problem and ignored the fundamentals and focuses on the way prices move. Renaissance makes thousands of trades a day on short time frames from hours to days and makes money on a little over 50% of their trades but their winners are bigger than their losers and the edge creates windfall profits on an astounding risk adjusted basis.
His money making fund is very similar to a casino exercising his mathematical edge over and over with small bets in relation to his total capital. The fund does use leverage but it is for trading in smaller diversified trades in volume not making large bets on any one trade in size.
Jim Simons was a master administrator in hiring the right people for his fund and leading them in the right direction for developing robust trading systems using scientific methods. One of the biggest edges his quant fund had was being one of the first to the market using his method, he had one of the most thorough historical price action data bases, and he removed the human weaknesses of emotions and ego out of his trading method.
If you love math and you love trading you will enjoy this book as it takes a deep dive into both. It is an easy and enjoyable read and is written more like a novel than a trading book.
I have read several hundred trading and investing books and I would put this one on my list of the top five trading books every written. This is a unique look into how quantitative trading works.
January 5, 2020
I thought that this was a shallow, poorly written story with one-dimensional characterizations and weak descriptions of technical concepts. Frankly, it felt like the author had 2-3 real sources with some grudges and decided to try and weave together a narrative with publicly available information and insufficient access.
Coming off of the two Rhodes books which shared a focus on technical topics with idiosyncratic savants as the main characters, I found Zuckermans' book extremely weak; it read more like a wikipedia page than a real story, and it felt like the characterizations were overwrought and subject to availability bias in the sources he had, many of whom felt like they had a grudge against the firm.
Going a level down, I don't think that Zuckerman sufficiently captures either the intrinsic motivation or joy of the characters or the complexity and depth of what they were doing. There was just something missing that killed the book for me.
Frankly, I wanted to learn more, but basically what I learned was that if you just sorta hire the smartest people (somehow) and walk around smoking cigarettes, eventually you can launch the Flatiron Institute (not even mentioned in the book, by the way), and sorta donate stuff to Democrats while your buddies donate to Republicans and maybe are the root of all evil, and also sometimes people work ridiculous hours in finance and yell at one another, because it can be stressful and also randomly you obtain ~30% ARR after 45% fees on a fund that just sorta does normal stuff. Also, like other quant firms exist and are the same, or different, and computational linguistics is similar to some of this, because of hidden Markov trees and stuff.
At the end of the day, I think that the core weakness of this book was that the author never really understood the technology in a way that allowed him to transmit the joy of invention and creation through to the reader. From what I can understand RenTech was really ahead of its times technically (one of the first places to be doing terabyte / petabyte-scale machine learning-style workflows), and I think that without that technical exploration as a first principle to drive the narrative or a real focus on a single person (Simons oddly just felt like he did very little, despite the fact that he obviously must have done quite a lot), the book was just flat and sloppy.
Coming off of the two Rhodes books which shared a focus on technical topics with idiosyncratic savants as the main characters, I found Zuckermans' book extremely weak; it read more like a wikipedia page than a real story, and it felt like the characterizations were overwrought and subject to availability bias in the sources he had, many of whom felt like they had a grudge against the firm.
Going a level down, I don't think that Zuckerman sufficiently captures either the intrinsic motivation or joy of the characters or the complexity and depth of what they were doing. There was just something missing that killed the book for me.
Frankly, I wanted to learn more, but basically what I learned was that if you just sorta hire the smartest people (somehow) and walk around smoking cigarettes, eventually you can launch the Flatiron Institute (not even mentioned in the book, by the way), and sorta donate stuff to Democrats while your buddies donate to Republicans and maybe are the root of all evil, and also sometimes people work ridiculous hours in finance and yell at one another, because it can be stressful and also randomly you obtain ~30% ARR after 45% fees on a fund that just sorta does normal stuff. Also, like other quant firms exist and are the same, or different, and computational linguistics is similar to some of this, because of hidden Markov trees and stuff.
At the end of the day, I think that the core weakness of this book was that the author never really understood the technology in a way that allowed him to transmit the joy of invention and creation through to the reader. From what I can understand RenTech was really ahead of its times technically (one of the first places to be doing terabyte / petabyte-scale machine learning-style workflows), and I think that without that technical exploration as a first principle to drive the narrative or a real focus on a single person (Simons oddly just felt like he did very little, despite the fact that he obviously must have done quite a lot), the book was just flat and sloppy.
February 21, 2021
THIS IS NOT A TECHY book. It's a BUSINESS book about a tech business & MUST read by everyone. A MASTERPIECE.
I first read about the Medallion fund in the WSJ a couple of years ago & was shocked. Who & how did this fund beat Warren Buffet, Peter Lynch et all, over the years? This book explains it all.
It's a SLOW read & peaks at the end. Be patient.
Why I loved it:
- It EXPOSES how entrepreneurs think. Jim & his crack tech team get their bets 50.75% right & that was enough to create Medallion! :) (It resonates with me, 'coz I run a biz that has lots of hits & misses)
- Amazing insights into the mind, highs & lows of Billionaire entrepreneurs. Even after being worth 20 Billion US$, Jim's heart sinks when the markets fall :)
- The ABSOLUTE TENACITY required to move things forward. As I completed this book, I thought I was still in kindergarten in terms of personal effort!
- The relentless need to keep improving things. At age 50, Jim looks like he hasn't got much achieved. It's goosebumpy all the way!
- You don't HAVE to be a domain expert to win. “Simons never took a single finance class, didn’t care very much for business, & until he turned 40, only dabbled in trading."
I first read about the Medallion fund in the WSJ a couple of years ago & was shocked. Who & how did this fund beat Warren Buffet, Peter Lynch et all, over the years? This book explains it all.
It's a SLOW read & peaks at the end. Be patient.
Why I loved it:
- It EXPOSES how entrepreneurs think. Jim & his crack tech team get their bets 50.75% right & that was enough to create Medallion! :) (It resonates with me, 'coz I run a biz that has lots of hits & misses)
- Amazing insights into the mind, highs & lows of Billionaire entrepreneurs. Even after being worth 20 Billion US$, Jim's heart sinks when the markets fall :)
- The ABSOLUTE TENACITY required to move things forward. As I completed this book, I thought I was still in kindergarten in terms of personal effort!
- The relentless need to keep improving things. At age 50, Jim looks like he hasn't got much achieved. It's goosebumpy all the way!
- You don't HAVE to be a domain expert to win. “Simons never took a single finance class, didn’t care very much for business, & until he turned 40, only dabbled in trading."
May 5, 2020
Renaissance Technologies (RenTech for short) was a quantitative trading firm started by Jim Simons in the late 1970’s before "quantitative trading" was really a thing. It is notorious for its astounding track record of returns (39.1% average returns net of fees) as well as its secrecy about how it achieves them.
The Man Who Solved the Market is written by a WSJ reporter who attempted to get the details. He mostly failed. Anyone hoping for deep insights into RenTech’s trading techniques won’t be particularly satisfied.
However, the book was an interesting history of quantitative trading and how the industry has evolved over the past four decades. It also offered some glimpses into what they did well. They hired and retained key employees particularly well (spoiler: paying them egregious sums of money works pretty well). They also had an impressive level of foresight into the role data would play in finance, building up a repository of historical market data that competitors have probably been lagging behind since the 80s.
The Man Who Solved the Market is written by a WSJ reporter who attempted to get the details. He mostly failed. Anyone hoping for deep insights into RenTech’s trading techniques won’t be particularly satisfied.
However, the book was an interesting history of quantitative trading and how the industry has evolved over the past four decades. It also offered some glimpses into what they did well. They hired and retained key employees particularly well (spoiler: paying them egregious sums of money works pretty well). They also had an impressive level of foresight into the role data would play in finance, building up a repository of historical market data that competitors have probably been lagging behind since the 80s.
December 21, 2019
The Man Who Solved The Market lets people take a peak inside the Renaissance Tech, the worlds most profitable hedge fund & the people behind it. RenTech beats many other managers like Warren Buffett, Peter Lynch, Paul Tudor Jones in terms of raw returns.
Zuckerman does a fine job of describing the people & story behind RenTech. Zuckerman describes James Simons the founder, Mercer, someone who supported Trump get to the White House & others who are responsible for collectively making over $100 Billion trading public markets.
This book & Loserthink both released on the same day & I had my hands full in reading them one after the other. Having a long train and then road trip also helped!
Zuckerman does a fine job of describing the people & story behind RenTech. Zuckerman describes James Simons the founder, Mercer, someone who supported Trump get to the White House & others who are responsible for collectively making over $100 Billion trading public markets.
This book & Loserthink both released on the same day & I had my hands full in reading them one after the other. Having a long train and then road trip also helped!
November 16, 2019
This book is an account of journey of Renaissance Technologies , a quant based hedge fund. This book does not contain any algorithms used by RenTech but lays out the thought process of it's founders in the form of a story. Normal traders like me can get intimidated by the ivy league degrees and cutting edge mathematics/ physics research scientist of the organization. But the story lays of struggles of the super smart guys and serves as an inspiration for developing own thought process and more importantly implementing it.
This book has anecdotes which form the basis of a gripping read. I won't be surprised if this is made into a movie in this age of machine learning and AI
This book has anecdotes which form the basis of a gripping read. I won't be surprised if this is made into a movie in this age of machine learning and AI
November 17, 2019
The book focus on Renaissance but goes beyond and describes also the Quant competition and the landscape over the past 50 years.
The personal lives of many partners and former partners of the firm is very well explored by the author and it feels like he had enough access and testimonies to be able to tell an honest narrative.
The book has some passages where the author insert some technical trading terms but anyone can enjoy it , even with no knowledge of quant strategies.
The chapter detailing Bon Mercer and his daughter Rebekah Mercer working with Steve Bannon to elect Trump and their closeness with the White House feels like a bonus to the overall arch or the book.
The personal lives of many partners and former partners of the firm is very well explored by the author and it feels like he had enough access and testimonies to be able to tell an honest narrative.
The book has some passages where the author insert some technical trading terms but anyone can enjoy it , even with no knowledge of quant strategies.
The chapter detailing Bon Mercer and his daughter Rebekah Mercer working with Steve Bannon to elect Trump and their closeness with the White House feels like a bonus to the overall arch or the book.
August 23, 2020
Ļoti interesanti krikumi par mašīnmācīšanos un finanšu tirgiem. Kārtējā non-fiction grāmata, kas varēja būt izcila 50 lpp. eseja, bet kļuva par 320 lpp. grāmatu, jo kaut kā jāiepārdod cietie vāki. Sāciet lasīt no 100. lpp. - tikai tad sāk parādīties patiešām vērtīgais info par Medallion Fund.
Džims Simonss atklājas kā ļoti emocionāli saprotams un iespaidīgs tēls, kurš māk vadīt sarežģīti vadāmus cilvēkus un sasniegt izcilus rezultātus.
Labi redzēt, cik līdzīgas ir ikdienas mašīnmācīšanās problēmas dažādās jomās - jaunu datu avotu medīšana, datu tīrīšana, signāla meklēšana, ātrāka apstrāde, ieviešana veidā, kas neiznīcina vērtīgo signālu.
Džims Simonss atklājas kā ļoti emocionāli saprotams un iespaidīgs tēls, kurš māk vadīt sarežģīti vadāmus cilvēkus un sasniegt izcilus rezultātus.
Labi redzēt, cik līdzīgas ir ikdienas mašīnmācīšanās problēmas dažādās jomās - jaunu datu avotu medīšana, datu tīrīšana, signāla meklēšana, ātrāka apstrāde, ieviešana veidā, kas neiznīcina vērtīgo signālu.
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