What do you think?
Rate this book
The Physics of Wall Street: A Brief History of Predicting the Unpredictable
After the economic meltdown of 2008, Warren Buffett famously warned, “beware of geeks bearing formulas.” But as James Weatherall demonstrates, not all geeks are created equal. While many of the mathematicians and software engineers on Wall Street failed when their abstractions turned ugly in practice, a special breed of physicists has a much deeper history of revolutionizing finance. Taking us from fin-de-siècle Paris to Rat Pack-era Las Vegas, from wartime government labs to Yippie communes on the Pacific coast, Weatherall shows how physicists successfully brought their science to bear on some of the thorniest problems in economics, from options pricing to bubbles. The crisis was partly a failure of mathematical modeling. But even more, it was a failure of some very sophisticated financial institutions to think like physicists. Models—whether in science or finance—have limitations; they break down under certain conditions. And in 2008, sophisticated models fell into the hands of people who didn’t understand their purpose, and didn’t care. It was a catastrophic misuse of science. The solution, however, is not to give up on models; it's to make them better. Weatherall reveals the people and ideas on the cusp of a new era in finance. We see a geophysicist use a model designed for earthquakes to predict a massive stock market crash. We discover a physicist-run hedge fund that earned 2,478.6% over the course of the 1990s. And we see how an obscure idea from quantum theory might soon be used to create a far more accurate Consumer Price Index. Both persuasive and accessible, The Physics of Wall Street is riveting history that will change how we think about our economic future.
286 pages, Hardcover
First published January 1, 2013
About the author
James Owen Weatherall
4 books40 followersJames Owen Weatherall is a physicist, philosopher, and mathematician. He holds graduate degrees from Harvard, the Stevens Institute of Technology, and the University of California, Irvine, where is presently an assistant professor of logic and philosophy of science. He has written for Slate and Scientific American.
Ratings & Reviews
Friends & Following
Create a free account to discover what your friends think of this book!
Community Reviews
Displaying 1 - 30 of 214 reviews
June 6, 2015
This book is a wonderful introduction to history of predicting stock prices using mathematics and concepts from physics. It is basically a history of pricing models; from the earliest mathematical models to the most modern ones. Of course, the best ones are maintained in secret by some super-secretive investment companies, for good reason. The only way a pricing model can be profitable is it to be better than most others being used.
The author, James Weatherall, has a PhD in physics, and is presently an assistant professor of logic and philosophy of science at the University of California, Irvine. He writes with clarity and an engaging style. His narrative follows a logical path, and does not take big diversions along the way.
Now, many of the subjects of this book are not physics at all, but applied mathematics. For example, the so-called "black box" model does not use any physics, but use purely statistical associations that are discovered algorithmically. Their name stems from the fact that they are opaque; they may make accurate predictions, but they offer no insight into the reasons for their predictions. Hence, it is difficult to judge how much confidence should be given to their results. But, for example, a model that predicts an investment strategy that returns a hundred times the S&P 500 over a fifteen-year period is nothing to be sneezed at.
Some of the models are definitely an application of physics concepts, such as the gauge theory model. I find if fascinating that this arcane physics concept has some practical applications in economics and predictions.
Some people blame these computer models for the disastrous economic downturns and stock market volatility that occur from time to time. While Weatherall sympathizes with this attitude, he wholeheartedly endorses the models, as they are simply tools. Sometimes, the assumptions and limitations of these tools are ignored, with dire consequences.
The author, James Weatherall, has a PhD in physics, and is presently an assistant professor of logic and philosophy of science at the University of California, Irvine. He writes with clarity and an engaging style. His narrative follows a logical path, and does not take big diversions along the way.
Now, many of the subjects of this book are not physics at all, but applied mathematics. For example, the so-called "black box" model does not use any physics, but use purely statistical associations that are discovered algorithmically. Their name stems from the fact that they are opaque; they may make accurate predictions, but they offer no insight into the reasons for their predictions. Hence, it is difficult to judge how much confidence should be given to their results. But, for example, a model that predicts an investment strategy that returns a hundred times the S&P 500 over a fifteen-year period is nothing to be sneezed at.
Some of the models are definitely an application of physics concepts, such as the gauge theory model. I find if fascinating that this arcane physics concept has some practical applications in economics and predictions.
Some people blame these computer models for the disastrous economic downturns and stock market volatility that occur from time to time. While Weatherall sympathizes with this attitude, he wholeheartedly endorses the models, as they are simply tools. Sometimes, the assumptions and limitations of these tools are ignored, with dire consequences.
May 27, 2013
The author is a physics professor and someone who holds academics in high regard. The latter becomes a big problem later on in the book.
The good chunk of the book is devoted to the history of how academic and finance intersect. The section on a Louis Bachelier, whose pioneering work was largely ignored by his peers, was particularly fascinating. Other interesting anecdotes include Edward Thorp, a mathematician who beat the casinos at blackjackHowever, and how the DuPont team that invented pantyhose came to head the Manhattan project. However, the ultimate problem is Weatherall's aim at linking research and success in finance and economics (i.e. predicting the unpredictable). He makes a ridiculous claim that all is needed to reshape the world's economic policies for the better, is an interdisciplinary conference (with physicists, of course), dubbed the New Manhattan Project.
The problem that Weatherall glossed over, is that academics haven't exactly been able to predict the unpredictable. Yes, there are a few hedge fund managers with strong academic backgrounds (see "The Quants: How a New Breed of Math Whizzes Conquered Wall Street and Nearly Destroyed It" by Scott Patterson), but they were not immune from catastrophic losses during the 2008 financial crisis. In fact, the two of the academic giants lauded by Weatherall, Merton and Scholes, were the key founders of Long-term Capital Management.
However, their roles in LTCM's collapse was barely mentioned in the book (basically, their mathematical model failed). Weatherall seems to claim that, science can be used to "crack" the problems in finance and economics, if only we put enough scientists (preferably physicists) together.
Ultimately, I am of the opinion that finance/economics are not scientific problems that can be solved, like a mathematical formula. If that were the case, we'd have more obscenely rich scientist-turned-hedge-fund-managers, or better economic policies derived from Kaynes and Freeman. Talib's "Black Swan" is much more appealing because it has the humility to concede that we cannot predict the unpredictable (therefore the Black Swans happen more frequently than mathematical models predict, e.g. LTCM and every financial crisis)
The good chunk of the book is devoted to the history of how academic and finance intersect. The section on a Louis Bachelier, whose pioneering work was largely ignored by his peers, was particularly fascinating. Other interesting anecdotes include Edward Thorp, a mathematician who beat the casinos at blackjackHowever, and how the DuPont team that invented pantyhose came to head the Manhattan project. However, the ultimate problem is Weatherall's aim at linking research and success in finance and economics (i.e. predicting the unpredictable). He makes a ridiculous claim that all is needed to reshape the world's economic policies for the better, is an interdisciplinary conference (with physicists, of course), dubbed the New Manhattan Project.
The problem that Weatherall glossed over, is that academics haven't exactly been able to predict the unpredictable. Yes, there are a few hedge fund managers with strong academic backgrounds (see "The Quants: How a New Breed of Math Whizzes Conquered Wall Street and Nearly Destroyed It" by Scott Patterson), but they were not immune from catastrophic losses during the 2008 financial crisis. In fact, the two of the academic giants lauded by Weatherall, Merton and Scholes, were the key founders of Long-term Capital Management.
However, their roles in LTCM's collapse was barely mentioned in the book (basically, their mathematical model failed). Weatherall seems to claim that, science can be used to "crack" the problems in finance and economics, if only we put enough scientists (preferably physicists) together.
Ultimately, I am of the opinion that finance/economics are not scientific problems that can be solved, like a mathematical formula. If that were the case, we'd have more obscenely rich scientist-turned-hedge-fund-managers, or better economic policies derived from Kaynes and Freeman. Talib's "Black Swan" is much more appealing because it has the humility to concede that we cannot predict the unpredictable (therefore the Black Swans happen more frequently than mathematical models predict, e.g. LTCM and every financial crisis)
April 24, 2013
The quote that stands out for me from this book is, “The business of prediction has become an industry.”
I am always tinkering around in Excel spreadsheets building models in my unsophisticated, non-formally trained manner, trying to predict everything from various customer behaviors at work to stock prices and lottery numbers in personal life. While I’ve had some success at work and on picking stocks that meet my goal of making a 5% profit in nine days or less (in which I consider myself a long-term day trader), I have not hit upon anything that helps with lottery numbers (obviously).
Anything related to successful modeling or predictions are always awe inspiring to me and I eagerly long to be one of those success stories by stumbling into the hidden pattern in the data. Oh, to find the secret key! The ability to live vicariously through successful individuals in this trade, is the reason this book originally appealed to me.
I thoroughly enjoyed this brief history of predicting the unpredictable . I originally gave this a 3-star rating. However, after coming back few days later to write these comments, I have now increased it to 4-stars because it has again encouraged me to continue to work on my models and more importantly. . .to dream. . . and discover.
I am always tinkering around in Excel spreadsheets building models in my unsophisticated, non-formally trained manner, trying to predict everything from various customer behaviors at work to stock prices and lottery numbers in personal life. While I’ve had some success at work and on picking stocks that meet my goal of making a 5% profit in nine days or less (in which I consider myself a long-term day trader), I have not hit upon anything that helps with lottery numbers (obviously).
Anything related to successful modeling or predictions are always awe inspiring to me and I eagerly long to be one of those success stories by stumbling into the hidden pattern in the data. Oh, to find the secret key! The ability to live vicariously through successful individuals in this trade, is the reason this book originally appealed to me.
I thoroughly enjoyed this brief history of predicting the unpredictable . I originally gave this a 3-star rating. However, after coming back few days later to write these comments, I have now increased it to 4-stars because it has again encouraged me to continue to work on my models and more importantly. . .to dream. . . and discover.
August 15, 2014
Journalistic wish-wash. Some stories are interesting for entertainment value but opinions by author ironically highlight his own lack of rigor.
January 26, 2018
A better review is worth putting up. One illustrious professor of finance wrote an 18-part blog series on why this is the worst book in the world, or at least arrogant and inaccurate (http://www.minyanville.com/business-n...). That series is indeed very informative; to date I haven't quite finished it, but I have finished the book and found it terrific (not knowing so much about economics). The former CFO of Microsoft (a former chair of NASDAQ) praises this work by James Owen Weatherall, agreeing from the back cover with several other luminaries, mostly in finance. Weatherall has a PhD in physics and teaches Logic and Philosophy of Science at UC Irvine. He interviewed all "physicist"-economists in question (he is a little too inclusive about physicists, for example calling the applied mathematician Benoit Mandelbrot a "physicist" to streamline his point) and had them read drafts for accuracy, or else found surviving family members or associates.
The style is easy to read. Equations turn books to depleted uranium on the shelves, but a few equations would have been nice. What drew me to this book was the possibility of learning more about the association between entropy/thermodynamics and real economies. Weatherall did not discuss the particular question I had, but information theory came in from several corners and filled out my appreciation of the subject. Not to mention: I know a great deal more - even with a few glossed-over simplifications, as pointed out carefully in the long critique linked above - about financial markets than I knew going in. A great deal more!
As the book's leading critic (see link above) says, The Physics of Wall Street is a good jumping-off point for a more in-depth correction of its oversights and simplifications. I feel that this fellow has slightly misunderstood the purpose and audience of the book. While the following statement is not always popular, there is an element of truth in it: teaching is often controlled lying. If Weatherall teaches by controlled lying, he makes a gentle and compelling introduction; if inadvertently by naive arrogance, the result is not dramatically different. It is Weatherall's opinion that traditional finance is closed to certain ways of thinking, and we need a kind of Manhattan Project to get more people brainstorming; the blog-series author takes this quite personally and returns the attack on physics departments. None of that is particularly relevant. It's just flavor. People glom onto opinions, especially after a major stock-market collapse, and everyone has opinions to offer.
The real purpose of the book is quite simply to show how physics enthusiasts, and ideas from physics, have unexpectedly contributed to economics. The point is not, as the critic has misinterpreted, to show that physicists have done all the work all along. Weatherall says otherwise repeatedly, throughout the book. He is very clear about his motivation in writing the book, and even his initial need for his advisor to say the idea for the book might have enough merit and material to pursue.
My five-star rating has more to do with how much I got from this book (and its long outside responses!) than with any pretense at measuring its objective value. (The same goes for every review I write with a score on it!)
The style is easy to read. Equations turn books to depleted uranium on the shelves, but a few equations would have been nice. What drew me to this book was the possibility of learning more about the association between entropy/thermodynamics and real economies. Weatherall did not discuss the particular question I had, but information theory came in from several corners and filled out my appreciation of the subject. Not to mention: I know a great deal more - even with a few glossed-over simplifications, as pointed out carefully in the long critique linked above - about financial markets than I knew going in. A great deal more!
As the book's leading critic (see link above) says, The Physics of Wall Street is a good jumping-off point for a more in-depth correction of its oversights and simplifications. I feel that this fellow has slightly misunderstood the purpose and audience of the book. While the following statement is not always popular, there is an element of truth in it: teaching is often controlled lying. If Weatherall teaches by controlled lying, he makes a gentle and compelling introduction; if inadvertently by naive arrogance, the result is not dramatically different. It is Weatherall's opinion that traditional finance is closed to certain ways of thinking, and we need a kind of Manhattan Project to get more people brainstorming; the blog-series author takes this quite personally and returns the attack on physics departments. None of that is particularly relevant. It's just flavor. People glom onto opinions, especially after a major stock-market collapse, and everyone has opinions to offer.
The real purpose of the book is quite simply to show how physics enthusiasts, and ideas from physics, have unexpectedly contributed to economics. The point is not, as the critic has misinterpreted, to show that physicists have done all the work all along. Weatherall says otherwise repeatedly, throughout the book. He is very clear about his motivation in writing the book, and even his initial need for his advisor to say the idea for the book might have enough merit and material to pursue.
My five-star rating has more to do with how much I got from this book (and its long outside responses!) than with any pretense at measuring its objective value. (The same goes for every review I write with a score on it!)
March 4, 2013
The book started nice but got worse from chapter to chapter. It should definitely have another title: Physicists of Wall Street. But even then: the author is loosing the path of the story after the first two chapters. It is nice to tell all these little stories how a physicist turns into a hedge fund manager but what does this really mean? Btw: being a physicist managing a VC fund myself.
Read
January 2, 2015Sort of like Michael Lewis finance journalism in tone but less skeptical of the whole enterprise. Less of a narrative, but a little better about getting into the gritty facts. As always, I'd like more math, but that wouldn't sell, would it?
Enjoyed.
Enjoyed.
November 24, 2014
This book won't get me rich : (
December 23, 2021
I picked up this book expecting it to be a primer on financial math, but although "physics" is plastered in the largest, uppercase font on the cover, this book is a history textbook more than anything -- a series of biographies like spines on a fishbone, each separate in origin but ultimately one way or another converge into the central vertebrae that is the development of quantitative finance. Not to say that this is a substandard book, but perhaps just not what I was looking for.
To be fair, the book does put forth a compelling storyline with intricate detail (enough to make me question how he knew a 19th century mathematician in his obscure phase as though he were a friend), and highlights the gargantuan role that mathematics and modelling has played in shaping the direction of finance with undeniable evidence (like the 1987 crash and black-scholes equation). If you're looking for a good story then you've got one.
Where it's lacking is in the actual "physics" part. At first it provides a reasonable intuition for Bachelier's random walk hypothesis and makes a reasonable leap to Osborne's revised log-normal model. But as the narrative progresses the math necessarily gets increasingly abstruse (as is always with math) and confidential (afterall, people make money using this math), in an effort to keep the book accessible much is cut out in explaining complicated concepts. Towards the end, only what is done is described -- explaining how it's done is a fruitless endeavour. But in all fairness this wasn't meant to be a math textbook, it's just my personal preference that it have delved further into the real math.
I think this book is useful for those who already have a background in financial math, who have a solid grasp of the current-day state of quantitative finance, looking to know more about how it came to be this way, rather than someone looking to learn about finance from square one.
To be fair, the book does put forth a compelling storyline with intricate detail (enough to make me question how he knew a 19th century mathematician in his obscure phase as though he were a friend), and highlights the gargantuan role that mathematics and modelling has played in shaping the direction of finance with undeniable evidence (like the 1987 crash and black-scholes equation). If you're looking for a good story then you've got one.
Where it's lacking is in the actual "physics" part. At first it provides a reasonable intuition for Bachelier's random walk hypothesis and makes a reasonable leap to Osborne's revised log-normal model. But as the narrative progresses the math necessarily gets increasingly abstruse (as is always with math) and confidential (afterall, people make money using this math), in an effort to keep the book accessible much is cut out in explaining complicated concepts. Towards the end, only what is done is described -- explaining how it's done is a fruitless endeavour. But in all fairness this wasn't meant to be a math textbook, it's just my personal preference that it have delved further into the real math.
I think this book is useful for those who already have a background in financial math, who have a solid grasp of the current-day state of quantitative finance, looking to know more about how it came to be this way, rather than someone looking to learn about finance from square one.
November 19, 2020
I'd give to the first three quarters 3.5 stars. The author, showing a talent to synthetize complex concepts in simple words, narrates in an engaging way the story of the key figures who started and have contributed to the field of financial analysis and prediction based on ideas and models coming from advanced physics and math.
It's interesting to note how almost all these bright minds were/are polymaths, and had/have an unusual and often difficult relationship with the academic world.
Also, the author did not limit the story strictly to the subject of finance, but used the occasion to refer to and explain key milestones in the history of modern physics/science, thus giving to the reader an abundant context to connect the dots, and to the book a wider scope than expected.
Unfortunately, the last chapters (among doomsday predictions that were very fashionable in 2008-2014 and turned out to be wrong, constant sales pitches for Weinstein's projects, weakly supported strong subjective opinions, and preachy, misguided criticisms of the way economics as a scientific community works) display a drop in quality, and I'd give them 2 stars.
It's interesting to note how almost all these bright minds were/are polymaths, and had/have an unusual and often difficult relationship with the academic world.
Also, the author did not limit the story strictly to the subject of finance, but used the occasion to refer to and explain key milestones in the history of modern physics/science, thus giving to the reader an abundant context to connect the dots, and to the book a wider scope than expected.
Unfortunately, the last chapters (among doomsday predictions that were very fashionable in 2008-2014 and turned out to be wrong, constant sales pitches for Weinstein's projects, weakly supported strong subjective opinions, and preachy, misguided criticisms of the way economics as a scientific community works) display a drop in quality, and I'd give them 2 stars.
November 8, 2014
I very much enjoyed this one. You don't have to be a physicist to catch all the author wants us to understand. He does a very good job of popularizing the science involved. There is more story-telling and history than science anyway, and that makes it quite entertaining. I particularly loved all the examples of borrowing between different disciplines like beating odds at gambling to predicting stress fractures in Kevlar to earthquakes to wall street and beyond. Quite fascinating and surprisingly took away the "ick" factor that I had previously associated with Wall Street quants.
May 11, 2023
Dos y media redondeadas a tres. Tiene cosas muy entretenidas, sobre todo al inicio, cuando nos cuenta cosas sobre el precocísimo Louis Bachelier (los precios son normales, siguen un random walk, un movimiento browniano), corregido y aumentado Maurie Osborne (los retornos son normales, lo que fuerza a los precios a ser lognormales), con posteriores adiciones de Mandelbrot (no son normales, hay un problema de fat tails, los cisnes negros so más habituales de lo que predice la teoría) y unos cuantos más (contando por supuesto a Thorpe y su sucesores, Black, Scholes y Merton, que derivaron la fórmula para poner precio a las opciones que ha sido usada mayoritariamente en el mundo desde entonces). Este inicio del libro está muy bien, si excluimos la labor de succión fina que el autor hace de Jim Simmons, CEO de Renaissance, para luego no volverlo a mencionar más que de pasada en las últimas páginas.
Tras una introducción MUY buena, cinco estrellas, el autor pasa a hablarnos del proyecto Manhattan y de la creación del nylon en Dupont y poco a poco va perdiendo fuelle, saltando de flor en flor (solo las flores buenas, porque cuando Scholes y Merton se dan la gran guaya con LTCM por culpa de sus modelos matemáticos que fallaron, al autor pasa de puntillas). El caso es que el autor (físico) solo se fija en las aportaciones al mercado que han hecho los físicos, y directamente ignora todos los demás avances.
En cuestión de divulgación científica, por cierto, el autor fracasa miserablemente al intentar explicar en términos de la calle lo que es la simetría gauge (ojo, no digo que sea fácil, digo que lo que deja el autor por escrito no merecía ser publicado).
Acaba el autor diciendo que lo que le hace falta al mundo es un segundo proyecto Manhattan en el que se junten unos cientos de físicos y "resuelvan" el problema del modelado de la economía. Se le va.
Recomiendo su lectura, pero con pinzas. La primera parte salva al libro.
Tras una introducción MUY buena, cinco estrellas, el autor pasa a hablarnos del proyecto Manhattan y de la creación del nylon en Dupont y poco a poco va perdiendo fuelle, saltando de flor en flor (solo las flores buenas, porque cuando Scholes y Merton se dan la gran guaya con LTCM por culpa de sus modelos matemáticos que fallaron, al autor pasa de puntillas). El caso es que el autor (físico) solo se fija en las aportaciones al mercado que han hecho los físicos, y directamente ignora todos los demás avances.
En cuestión de divulgación científica, por cierto, el autor fracasa miserablemente al intentar explicar en términos de la calle lo que es la simetría gauge (ojo, no digo que sea fácil, digo que lo que deja el autor por escrito no merecía ser publicado).
Acaba el autor diciendo que lo que le hace falta al mundo es un segundo proyecto Manhattan en el que se junten unos cientos de físicos y "resuelvan" el problema del modelado de la economía. Se le va.
Recomiendo su lectura, pero con pinzas. La primera parte salva al libro.
July 16, 2024
"it was good, but got less good, but was decent at the end"
July 10, 2014
The role that Math & Physics plays on Wall Street has a controversial and complicated history. This book was a fun read and helped provide an historical context to place people like Thorp, Black, Simons, Mandelbrot and others from just the criticisms or praises I've heard/read elsewhere about them. In the controversy surrounding the EMH (Efficient Markets Hypothesis), the point that Weatherall makes about the Scientific Process as applied in the Financial Markets is a good one:
"...the methodology in action: one uses simplifying assumptions to make a problem tractable and solve it. Then, once you see how your solution works, you can double back and begin asking what happens when you play with your assumptions. Sometimes you realize that your original solution is no good, because it depends too heavily on assumptions that never really apply; other times, you discover that the solution is pretty good but can be improved in simple ways; and other times still, you realize that your solution is great under certain circumstances, but you need to think about what to do when those circumstances don’t apply." [Weatherall, James Owen (2013-01-08). The Physics of Wall Street: A Brief History of Predicting the Unpredictable (p. 209). Houghton Mifflin Harcourt. Kindle Edition.]
This seems like a reasonable assertion and builds on the point made earlier in the book (something that seems lost perhaps on many Quants and those that use their models) regarding the distinction between a model and a theory:
"A theory, at least as it is usually thought of in physics, is an attempt to completely and accurately describe some feature of the world. A model, meanwhile, is a kind of simplified picture of how a physical process or system works." [Weatherall, James Owen (2013-01-08). The Physics of Wall Street: A Brief History of Predicting the Unpredictable (p. 20). Houghton Mifflin Harcourt. Kindle Edition.]
And whether one looks at the events of the Great Financial Crisis and calls into question whether Physics/Mathematics is beneficial or not, the warning at the close of the book provided by the reference to Derman and Wilmott's Manifesto is a sobering reminder:
"Derman and Wilmott, in their Manifesto, make this point quite clearly. We should never mistake a good model for the “truth” about financial markets. The most important reason for this is that markets are themselves evolving, in response to changing economic realities, new regulations, and, perhaps most importantly, innovation ." [Weatherall, James Owen (2013-01-08). The Physics of Wall Street: A Brief History of Predicting the Unpredictable (p. 209). Houghton Mifflin Harcourt. Kindle Edition. ]
This book would make an excellent read for anyone remotely interested in the underpinnings of a still unresolved debate within the halls of Wall Street and Academia. And, as a side note, if you have ever heard the Hedge Fund named Renaissance mentioned in hushed and reverent tones the close of the book should inspire you to read further...
"The people charged with running the world’s economies should be as good as Renaissance. In fact, they should be better." [Weatherall, James Owen (2013-01-08). The Physics of Wall Street: A Brief History of Predicting the Unpredictable (p. 225). Houghton Mifflin Harcourt. Kindle Edition. ]
"...the methodology in action: one uses simplifying assumptions to make a problem tractable and solve it. Then, once you see how your solution works, you can double back and begin asking what happens when you play with your assumptions. Sometimes you realize that your original solution is no good, because it depends too heavily on assumptions that never really apply; other times, you discover that the solution is pretty good but can be improved in simple ways; and other times still, you realize that your solution is great under certain circumstances, but you need to think about what to do when those circumstances don’t apply." [Weatherall, James Owen (2013-01-08). The Physics of Wall Street: A Brief History of Predicting the Unpredictable (p. 209). Houghton Mifflin Harcourt. Kindle Edition.]
This seems like a reasonable assertion and builds on the point made earlier in the book (something that seems lost perhaps on many Quants and those that use their models) regarding the distinction between a model and a theory:
"A theory, at least as it is usually thought of in physics, is an attempt to completely and accurately describe some feature of the world. A model, meanwhile, is a kind of simplified picture of how a physical process or system works." [Weatherall, James Owen (2013-01-08). The Physics of Wall Street: A Brief History of Predicting the Unpredictable (p. 20). Houghton Mifflin Harcourt. Kindle Edition.]
And whether one looks at the events of the Great Financial Crisis and calls into question whether Physics/Mathematics is beneficial or not, the warning at the close of the book provided by the reference to Derman and Wilmott's Manifesto is a sobering reminder:
"Derman and Wilmott, in their Manifesto, make this point quite clearly. We should never mistake a good model for the “truth” about financial markets. The most important reason for this is that markets are themselves evolving, in response to changing economic realities, new regulations, and, perhaps most importantly, innovation ." [Weatherall, James Owen (2013-01-08). The Physics of Wall Street: A Brief History of Predicting the Unpredictable (p. 209). Houghton Mifflin Harcourt. Kindle Edition. ]
This book would make an excellent read for anyone remotely interested in the underpinnings of a still unresolved debate within the halls of Wall Street and Academia. And, as a side note, if you have ever heard the Hedge Fund named Renaissance mentioned in hushed and reverent tones the close of the book should inspire you to read further...
"The people charged with running the world’s economies should be as good as Renaissance. In fact, they should be better." [Weatherall, James Owen (2013-01-08). The Physics of Wall Street: A Brief History of Predicting the Unpredictable (p. 225). Houghton Mifflin Harcourt. Kindle Edition. ]
July 22, 2021
Just a couple of negative to start this review off salty. 1st I think everyone knows that for non-fiction authors are recommended to keep a human focus or make an informative piece about "people". How this is done varies between authors but I found the approach in this book a little bit to formulaic and honestly a little Biblical (let me explain). Each chapter started with a target usually an academic of some kind, and then prompted a family tree of inspiration - something like here is Jane Smith who convinced her then boyfriend to study the stock market, the boyfriend who was supervised by the legendary Leeroy Jenkins, who uknowningly replicated the thesis of Marcus Aurelis back in the BC.
Anyway the point is this tome was a little too human focussed and a little too focussed on the pin and sring board of who theorized what, rather than focussing on the actual theories!!
Secondly I felt Weatherall was a bit cheeky in the beginning, introducing Renaisance Investing - allegedly the most successful hedge-fund in the world (mysteriously only available to invest in if you work there) only to effectively never mention them again until the end of the book. The cheeky part being basically the implication that discussing the physics of wall street will lead to that topic, but no it was just a tease - the majority of the book is about the individual physists and how they got involved in finance not really specifically about their success or whatever.
OK deep breath.
Those criticisms aside the book is actually pretty good - despite my whinging the book was actually an enjoyable read and did contain some very interesting pieces on stock prices. In particular the chapters about distributions other than normal, and the physics of rupturing.
I guess given the mixed review above what is really hard to who to recommend this book to. It's not really thick with investment advice, and probably somewhat limited with physics material (compared to something a physics major would be keen on). So Physics of Wall St is probably more for the hisotrical expert who likes to piece different topics together to make sense of them.
All in all, not upset that I read the piece - and again despite a couple of negative points really is well written and has some valuable points contained within.
Anyway the point is this tome was a little too human focussed and a little too focussed on the pin and sring board of who theorized what, rather than focussing on the actual theories!!
Secondly I felt Weatherall was a bit cheeky in the beginning, introducing Renaisance Investing - allegedly the most successful hedge-fund in the world (mysteriously only available to invest in if you work there) only to effectively never mention them again until the end of the book. The cheeky part being basically the implication that discussing the physics of wall street will lead to that topic, but no it was just a tease - the majority of the book is about the individual physists and how they got involved in finance not really specifically about their success or whatever.
OK deep breath.
Those criticisms aside the book is actually pretty good - despite my whinging the book was actually an enjoyable read and did contain some very interesting pieces on stock prices. In particular the chapters about distributions other than normal, and the physics of rupturing.
I guess given the mixed review above what is really hard to who to recommend this book to. It's not really thick with investment advice, and probably somewhat limited with physics material (compared to something a physics major would be keen on). So Physics of Wall St is probably more for the hisotrical expert who likes to piece different topics together to make sense of them.
All in all, not upset that I read the piece - and again despite a couple of negative points really is well written and has some valuable points contained within.
November 22, 2014
I was going to give this book 3 stars as I was not particularly impressed. Midway through the book, I could already see that it had two very big flaws.
First, there's not as much meat as I was hoping for. In particular, he goes in for very long tangents unrelated to Wall Street, e.g., the creation of nylon and the Manhattan Project. Those are great topics, but if I wanted to read about that there are many fine books about the Manhattan Project (don't know about the creation of nylon). I wanted to read about the physics of Wall Street.
Second, he is extremely overly enamored with the idea of the use of physics in financial markets. He strongly implies that if you have the right model you can predict financial markets. He talks about randomness a lot, but he seems to be thinking of it as if it were statistical mechanics, where exact predictions can nevertheless be made. He remains blissfully unaware of the nature of financial risk and the unpredictability (rather than randomness) of financial markets.
However, what made him lose one more star was his epilogue. He quotes Taleb and his mistrust of financial models. I am not a fan of Taleb, whose writings consist mainly of belaboring the bleeding obvious. However, the obvious point about extreme fat tails and the unpredictability of extreme events seems to have totally eluded the author. He actually reasons by analogy that if Taleb were right then we'd never build a skyscraper because it could be hit by a meteor. At the risk of breaking out the hand-puppets for Dr. Weatherall, the difference between those two situations is obvious. A meteor striking a skyscraper is an externality. The engineering models used in constructing the building never intended for the building to survive a meteor impact. Financial extreme events, on the other hand, are an intrinsic part of what's being modeled. Surviving October 1987 or the Great Recession is precisely what Weatherall's mythical models are supposed to do.
Bottom line: This book is not worth reading, either by the layman or the specialist.
First, there's not as much meat as I was hoping for. In particular, he goes in for very long tangents unrelated to Wall Street, e.g., the creation of nylon and the Manhattan Project. Those are great topics, but if I wanted to read about that there are many fine books about the Manhattan Project (don't know about the creation of nylon). I wanted to read about the physics of Wall Street.
Second, he is extremely overly enamored with the idea of the use of physics in financial markets. He strongly implies that if you have the right model you can predict financial markets. He talks about randomness a lot, but he seems to be thinking of it as if it were statistical mechanics, where exact predictions can nevertheless be made. He remains blissfully unaware of the nature of financial risk and the unpredictability (rather than randomness) of financial markets.
However, what made him lose one more star was his epilogue. He quotes Taleb and his mistrust of financial models. I am not a fan of Taleb, whose writings consist mainly of belaboring the bleeding obvious. However, the obvious point about extreme fat tails and the unpredictability of extreme events seems to have totally eluded the author. He actually reasons by analogy that if Taleb were right then we'd never build a skyscraper because it could be hit by a meteor. At the risk of breaking out the hand-puppets for Dr. Weatherall, the difference between those two situations is obvious. A meteor striking a skyscraper is an externality. The engineering models used in constructing the building never intended for the building to survive a meteor impact. Financial extreme events, on the other hand, are an intrinsic part of what's being modeled. Surviving October 1987 or the Great Recession is precisely what Weatherall's mythical models are supposed to do.
Bottom line: This book is not worth reading, either by the layman or the specialist.
January 21, 2014
To be perfectly honest, I don't have the slightest idea who is the target audience of this book. I doubt it is economist, because the Econ-theory explained in the book is at best rudimentary and at worst miss guided. And it can't be the general public because of the authors gliding over the more complex mathematics. Ergo must the target audience be physicists that are looking for a historical overview of the influence of physics on to economics.
One thing is sure, the author isn't succeeding in his stated goal of convincing the readers that the solution to the problems of bad models are more models.
One thing is sure, the author isn't succeeding in his stated goal of convincing the readers that the solution to the problems of bad models are more models.
November 8, 2014
I don't understand the purpose of this book. I though it would describe how physicists gave up science for Wall Street. It comes across as the type of book you'd find in a college's career center.
January 2, 2018
It's the relationship among math, finance, physics, and chaos fractals.
December 23, 2021
reading notes:
random walk hypothesis/ efficient market hypothesis: if you have a market consisting of many informed investors who are constantly agreeing on the prices at which trades should occur, the current price of a stock can be interpreted as the price at which there are just as many informed people willing to bet that the price will go up as are willing to bet that the price will go down. (ie the probability of the stock ticking up and the probability of the stock ticking down are both 50%.)
^the normal distribution he described for stock prices worked only under very unusual circumstances where there was little variations in prices
Osborne: returns, not prices are normally distributed.
Mandelbrot: financial markets are too wild. financial markets are dominated by extremes and intuitive ideas about normal distribution suck.
+ Taleb's argument: markets are too wild to be tamed by physicists. extreme events are what really matter and they are precisely what models are unable to anticipate.
The Prediction company: showed how physics can be used to fill in the gaps by using black box models to identify local, short-term inefficiencies and capitalize on them as quickly as possible—essentially using physics to be the most sophisticated investors in the market.
Sornette: took Mandelbrot’s observation that in wildly random markets, extreme events like market crashes have dominating effects, and tried to predict these catastrophes.
Models always have assumptions; it is up to the users to pay attention to whether those assumptions hold. Markets crashed cuz financial institutions failed to qn assumptions and resist complacency.
random walk hypothesis/ efficient market hypothesis: if you have a market consisting of many informed investors who are constantly agreeing on the prices at which trades should occur, the current price of a stock can be interpreted as the price at which there are just as many informed people willing to bet that the price will go up as are willing to bet that the price will go down. (ie the probability of the stock ticking up and the probability of the stock ticking down are both 50%.)
^the normal distribution he described for stock prices worked only under very unusual circumstances where there was little variations in prices
Osborne: returns, not prices are normally distributed.
Mandelbrot: financial markets are too wild. financial markets are dominated by extremes and intuitive ideas about normal distribution suck.
+ Taleb's argument: markets are too wild to be tamed by physicists. extreme events are what really matter and they are precisely what models are unable to anticipate.
The Prediction company: showed how physics can be used to fill in the gaps by using black box models to identify local, short-term inefficiencies and capitalize on them as quickly as possible—essentially using physics to be the most sophisticated investors in the market.
Sornette: took Mandelbrot’s observation that in wildly random markets, extreme events like market crashes have dominating effects, and tried to predict these catastrophes.
Models always have assumptions; it is up to the users to pay attention to whether those assumptions hold. Markets crashed cuz financial institutions failed to qn assumptions and resist complacency.
August 22, 2024
Interesting mathematics and history, it’s beautiful how the study of the movement of particles can also apply to financial markets(professor hsu said only somewhat tho 🙏). Although, I don’t believe financial markets can be solved like problems in physics because financial markets are not governed by the laws of nature. Instead, they are governed by the laws of government regulatory bodies. However, I agree with Weatherall’s sentiment that advancement in financial modeling should be to guide policymaking for the common good. Mathematical finance is cool but it shouldn’t be dedicated resources if its only purpose is to make wealthy people more money.
December 10, 2019
As a physicist I appreciate the focus on just physicists contributions to finance, while not hiding the fact that economists naturally have contributed as well. I think the book as a whole is honest in not neglecting the role of social science in shaping, understanding, and exploiting financial markets - while catering to physics nerds. Most of it I had never thought or heard about before. Some of the people I have heard about before, and their way of exploiting the markets, but others as also indicated, I think gets less praise than deserved. Good job science!
February 20, 2018
Loved this book. While being a book on how finance was influenced by physics it managed to get me really interested in some physics concepts. The history of how physicists got involved in finance is very interesting by itself.
May 31, 2019
The book is absolutely unpredictable.
November 17, 2019
caution: giving books like this to your kids or students could make them addicted to math and physics!
February 9, 2020
An attempt to connect physics and mathematics to finance. I found it a bit disappointing and can't explain why.
April 14, 2013
A great primer or history of the mathematics of finance, and the interplay between theory and empirical results. This book does a good job of showing how scientific economic theories are intuited and build upon one another, and how their complexity increases with the maturity of the field. Clearly written, with well illustrated connections between the principal actors and suggestions of their motivations. There is a surprisingly deep connection between physics and quantitative economics--and we shouldn't put [all] the blame of recent economic problems at the feet of the so-called quants. Unfortunately there were very few actual equations printed--I would not have minded to see some math--but the theories were all generally explained using intuitive metaphors, and the figures at least were instructive.
A chapter near the end of the book introduces gauge theory without doing a very thorough job of telling what the implications are, or of how this could be used to make money, or predict a market--which all of the other chapters and methods do. It was said that this might best have an impact on public policy. In the epilogue the author writes that gauge theory was mentioned as a possible new direction for economics to go--it was one of many areas of interest in economic analysis, but not necessarily one that will 'win' or be widely used. This seems a little speculative or premature to include in the book's analysis, and, as he mentions, with the sluggish inertia of economic policy it seems like we'll have a long time to wait before it might pay off.
I would have liked to hear something about high-frequency trading, something commonly used to demonize quants that I'm still unsure of the benefits of (societally, or to the market--I'm sure individuals can use high-frequency trading much to their advantage). I also think some game theoretic ideas might help elucidate some trading behaviors, and perhaps addressing how feedback of these schemes affects the markets (though this was probably included in predicting market instability--the dragon kings--if not elsewhere). Perhaps I'll peruse the notes and references section a little better to see if there's a suggested book for continuing this analysis.
I was encouraged to read this book after seeing the author, James Owen Weatherall, give a very captivating, multidisciplinary lecture on the nature of the relationship between Newton's and Einstein's laws of gravity--at a philosophy seminar, of all places. I hope he continues to write about multi-field-spanning ideas!
A chapter near the end of the book introduces gauge theory without doing a very thorough job of telling what the implications are, or of how this could be used to make money, or predict a market--which all of the other chapters and methods do. It was said that this might best have an impact on public policy. In the epilogue the author writes that gauge theory was mentioned as a possible new direction for economics to go--it was one of many areas of interest in economic analysis, but not necessarily one that will 'win' or be widely used. This seems a little speculative or premature to include in the book's analysis, and, as he mentions, with the sluggish inertia of economic policy it seems like we'll have a long time to wait before it might pay off.
I would have liked to hear something about high-frequency trading, something commonly used to demonize quants that I'm still unsure of the benefits of (societally, or to the market--I'm sure individuals can use high-frequency trading much to their advantage). I also think some game theoretic ideas might help elucidate some trading behaviors, and perhaps addressing how feedback of these schemes affects the markets (though this was probably included in predicting market instability--the dragon kings--if not elsewhere). Perhaps I'll peruse the notes and references section a little better to see if there's a suggested book for continuing this analysis.
I was encouraged to read this book after seeing the author, James Owen Weatherall, give a very captivating, multidisciplinary lecture on the nature of the relationship between Newton's and Einstein's laws of gravity--at a philosophy seminar, of all places. I hope he continues to write about multi-field-spanning ideas!
February 18, 2015
As a history book, The Physics of Wall Street is interesting enough, in a trivia night sort of way. I learned lots of interesting little tidbits and enjoyed most of the book. My alarm bells were silently ringing throughout, but then they blasted a hole in my eardrums when Weatherall implied that physicists studying chaos theory introduced the idea that an economy was the sum of individual parts to financiers, who though it was the future, and then to economists, who thought it was "nonsense." It was all down hill from there, especially during the epilogue, as the author attempts and fails to take on Nassim Taleb's Black Swan argument with, "since we can't trust models to catch everything we shouldn't drive on bridges.", ignores or isn't familiar with Mises/Hayek's "the knowledge problem" and finally goes on to suggest that central banks, the IMF, or whoever else should dole out the necessary money to fund an "economic Manhattan Project" where the best and brightest of physics can mingle with economists and bankers to create and modify economic/market/finance models. If you read this book, skip the epilogue.
July 13, 2018
A fun, readable history of the influence of physics on finance. Well-written and flows very well, essentially a collection of vignettes. The thesis is relatively simple but in our days contrarian-financial models should not be abandoned, but used with an eye towards improvement and with some knowledge of their limitations.
The book is an interesting exploration of both the financial ideas that physicists brought to wall street (Weatherall does a good job of explaining the ideas in non-technical terms), as well as the sociology of physics and finance. For example, the "father" of modern mathematical finance, a frenchman named Bachelier, laid down the foundations of finance almost a century ago (including random walk, Brownian motion, normally distributed price, martingales and even a proto-EMH. He argued that prices were random because news is random, and prior knowledge is already "priced in"), but because the application of math to finance was unfashionable at the time (at the time the academic circles focused on abstract math), his work never received the support or wide-spread recognition it should have. In contrast, Osborne, another physicist turned financial mathematician came of age after the synthesis of basic research and industrial support (Dupont's nylon and the Manhattan Project) already occurred, allowing his somewhat aimless research to occur. Similarly, Black of Black-Scholes became so celebrated because at the time, the powers that be were looking to start a derivatives market, and the end of the Bretton Woods system created floating exchange rates that would led to an explosion of currency derivatives. Similarly, Weatherall argues that Malaney's proposal to use gauge theory (a physics concept) to measure inflation, was sunk by academics who were tasked with ad hocing a method to measure CPI with the goal of reducing social security payouts. Weatherall thinks that physicists can be very useful in this sense, by injecting fresh ways and more nuanced understanding into the "old boy's club" of economic academia. A particularly promising example is the importation of how tanks explode and when bubbles burst (both study how the appearance of coordination between random fissures can lead to catastrophic failure similar to herding behavior, what Sornette calls dragon king theory, the idea that dragon kings can be predicted by certain periodic indica). Another example cited, the enormous success of Renaissance, which hires no economics or finance students, only those trained in mathematics and physics (though the secrecy of how Renaissance makes its money, makes discussions of its strategies rather speculative [a similar complaint occurs for "more money than god"]. This is the same complaint I have about the chapter on the "prediction company". Weatherall discusses how the hedge fund made money applying chaos theory concepts, such as attractors and initial conditions to pioneer black box statistical modeling [mostly off of statistical correlations without conjectures about underlying models], but admits that the firm is rather secretive [making the firm's success itself...a black box].).
I particularly liked the treatment of the simplifying assumptions found in models. There is I think, a tendency for detractors and pundits to dismiss a model by its assumptions alone. Weatherall makes the good point that the process of modeling is iterative, and that good modelers recognize their assumptions and improve on them. This happened with Edward Thorp, who improved on a blackjack model by realizing that cards dealt were not independent but actually dependent on the deck (starting the tactic of cardcounting). More dramatic is the story of the normal curve. Bachelier assumed that prices were normally distributed, but this lead to oddities such as negative prices. Osborne recognized that it was not prices, but returns that were normally distributed, implying a log-normal price distribution. Mandelbrot argued that actual market returns are not normal distributions but levy-stable distributions with fatter tails than the normal distribution (later research indicated that this, was also not technically correct), and as a consequence did not converge towards an average (reviewed also of course, is Mandelbrot's work on fractals and measurement theory). Weatherall makes the good point that, financial academia properly set aside Mandelbrot's discovery and used the simplifying assumption that returns were normally distributed in order to build more knowledge. At the time, it was unclear how to incorporate or even work with Mandelbrot's levy-stable distributions. However, as Weatherall notes, the market's volatility smile after 87' (which Weatherall interprets as the market's belief that out the money options were worth more than what Black-Scholes predicted) and O'Connor's modifications to the Black-Scholes model were indications that practitioners had indeed considered challenging the normal distribution assumption. By doing so, they played the role of "smart money" that EMH assumes.
The book concludes with three lessons about finance. 1) The best models are not ignorant of human nature but attempt to incorporate them (despite behavioral economics attacks on models, they themselves often produce models). For example, Osborne's conjecture that returns were log-normal was inspired by an old psychological experiment that people changes in sensations based on the starting sensation. 2) The misuse of models does not justify their wholesale abandonment, only that the limitations of models be recognized and improved on (contra Taleb). 3) Complicated financial instruments such as derivatives are tools, that be used correctly for good or incorrectly for bad.
A somewhat miscellaneous fact I find interesting, is the idea to only bet a fraction of wealth by advantage/payout as an optimal betting strategy.
A great book for anyone looking for a nuanced but non-technical view of finance, and a good counterweight to the very opinionated pundits that seem to have sprung up post-2008 like daisies. Not to mention, very enjoyable to read, both in readability and entertainment value.
The book is an interesting exploration of both the financial ideas that physicists brought to wall street (Weatherall does a good job of explaining the ideas in non-technical terms), as well as the sociology of physics and finance. For example, the "father" of modern mathematical finance, a frenchman named Bachelier, laid down the foundations of finance almost a century ago (including random walk, Brownian motion, normally distributed price, martingales and even a proto-EMH. He argued that prices were random because news is random, and prior knowledge is already "priced in"), but because the application of math to finance was unfashionable at the time (at the time the academic circles focused on abstract math), his work never received the support or wide-spread recognition it should have. In contrast, Osborne, another physicist turned financial mathematician came of age after the synthesis of basic research and industrial support (Dupont's nylon and the Manhattan Project) already occurred, allowing his somewhat aimless research to occur. Similarly, Black of Black-Scholes became so celebrated because at the time, the powers that be were looking to start a derivatives market, and the end of the Bretton Woods system created floating exchange rates that would led to an explosion of currency derivatives. Similarly, Weatherall argues that Malaney's proposal to use gauge theory (a physics concept) to measure inflation, was sunk by academics who were tasked with ad hocing a method to measure CPI with the goal of reducing social security payouts. Weatherall thinks that physicists can be very useful in this sense, by injecting fresh ways and more nuanced understanding into the "old boy's club" of economic academia. A particularly promising example is the importation of how tanks explode and when bubbles burst (both study how the appearance of coordination between random fissures can lead to catastrophic failure similar to herding behavior, what Sornette calls dragon king theory, the idea that dragon kings can be predicted by certain periodic indica). Another example cited, the enormous success of Renaissance, which hires no economics or finance students, only those trained in mathematics and physics (though the secrecy of how Renaissance makes its money, makes discussions of its strategies rather speculative [a similar complaint occurs for "more money than god"]. This is the same complaint I have about the chapter on the "prediction company". Weatherall discusses how the hedge fund made money applying chaos theory concepts, such as attractors and initial conditions to pioneer black box statistical modeling [mostly off of statistical correlations without conjectures about underlying models], but admits that the firm is rather secretive [making the firm's success itself...a black box].).
I particularly liked the treatment of the simplifying assumptions found in models. There is I think, a tendency for detractors and pundits to dismiss a model by its assumptions alone. Weatherall makes the good point that the process of modeling is iterative, and that good modelers recognize their assumptions and improve on them. This happened with Edward Thorp, who improved on a blackjack model by realizing that cards dealt were not independent but actually dependent on the deck (starting the tactic of cardcounting). More dramatic is the story of the normal curve. Bachelier assumed that prices were normally distributed, but this lead to oddities such as negative prices. Osborne recognized that it was not prices, but returns that were normally distributed, implying a log-normal price distribution. Mandelbrot argued that actual market returns are not normal distributions but levy-stable distributions with fatter tails than the normal distribution (later research indicated that this, was also not technically correct), and as a consequence did not converge towards an average (reviewed also of course, is Mandelbrot's work on fractals and measurement theory). Weatherall makes the good point that, financial academia properly set aside Mandelbrot's discovery and used the simplifying assumption that returns were normally distributed in order to build more knowledge. At the time, it was unclear how to incorporate or even work with Mandelbrot's levy-stable distributions. However, as Weatherall notes, the market's volatility smile after 87' (which Weatherall interprets as the market's belief that out the money options were worth more than what Black-Scholes predicted) and O'Connor's modifications to the Black-Scholes model were indications that practitioners had indeed considered challenging the normal distribution assumption. By doing so, they played the role of "smart money" that EMH assumes.
The book concludes with three lessons about finance. 1) The best models are not ignorant of human nature but attempt to incorporate them (despite behavioral economics attacks on models, they themselves often produce models). For example, Osborne's conjecture that returns were log-normal was inspired by an old psychological experiment that people changes in sensations based on the starting sensation. 2) The misuse of models does not justify their wholesale abandonment, only that the limitations of models be recognized and improved on (contra Taleb). 3) Complicated financial instruments such as derivatives are tools, that be used correctly for good or incorrectly for bad.
A somewhat miscellaneous fact I find interesting, is the idea to only bet a fraction of wealth by advantage/payout as an optimal betting strategy.
A great book for anyone looking for a nuanced but non-technical view of finance, and a good counterweight to the very opinionated pundits that seem to have sprung up post-2008 like daisies. Not to mention, very enjoyable to read, both in readability and entertainment value.
January 22, 2015
The Physics of Wall Street: A Brief History of Predicting the Unpredictable by James Owen Weatherall was an interesting exploration of the history of probability, economics, and physics and how scholars in all those fields have crossed discipline lines and collaborated to understand and predict economic forces. I especially enjoyed how the author gave the back story for each of the people he highlighted. This book also explained how buying short can be profitable in a way that I finally understand. I have carefully read other explanations of the concept, but until now I remained ignorant and mystified by the process. As he did with that concept, he explained the discoveries of these physicist economists in ways that made them accessible to my layman's thinking. I highly recommend this listen to those fascinated by the processes of discovery.
Displaying 1 - 30 of 214 reviews