It is not easy to come up with star ratings for this book. I will split the difference between two and four stars. Here is why...
On one hand, I consider it to be a chronology of scientific efforts to predict markets beginning as early as the 18th Century, all the way up to 2012. As such, it is very interesting in terms of some the best known historical names dabbling in it. The storytelling in the book is not very good, but despite that it kept my interest through many chapters.
On the other hand, I consider this book to be an attempt to explain (to the layman) how science can be used to predict markets. To that end, the examples of Simons and Sornette (and their spectacular success on Wall Street) are presented without going into details. One cannot justify everything by the brilliance of these men alone. If they indeed were successful based on their knowledge of physics, how they managed to do that should have been analyzed in the book. Instead, the author takes a very long-winded tour of random statistical distributions starting with Gaussians, then he moves on to Cauchy distributions and other fat-tailed distributions, and how they may be relevant to markets. If that was all there is for the scientific methodology of market prediction, you would not need physicists like Simons and Sornette. Anybody with some basic math and statistics will do fine. The physicists do far more than that, and none of that was discussed in the book. They come up with models of dynamic market balance, they convert these models to differential equations to be solved, and they (approximately) solve them (on fast super-computers.) It would have been fascinating if the author had any details available on that subject.
On the other hand, this book discusses a fascinating question on and off many times: can markets really be predicted? All indications are that markets can be predicted by sophisticated mathematical models (done by physicists) most of the time (when markets behave normally.) But there are times when markets do something really wild. The market crashes of 1929, 1989, 1997, and 2007 are examples. The real question is this: can a market crash be predicted a year in advance? The author discusses this topic too and tries to explain it as reaching the critical point when some rapid and discontinuous change takes place. The physics is very rich in well understood critical phenomena, many of which can be applied to markets. That's where the non-linear dynamics comes in. I believe (I don't know this for a fact) that some of the physicists on Wall Street can predict a major market crash several days (or even possibly weeks) ahead. But they can't do that a year in advance. The non-linear dynamics is notoriously sensitive to initial conditions, and the quality of the prediction deteriorates as we project farther and farther out into the future.
On the other hand, this book never discusses in detail one of the major dilemmas of market prediction. We (physicists) take great delight in discovering the laws of nature so that we can predict how it behaves. In this endeavor, we tacitly assume that nature continues to behave in the same manner before and after our discovery. The fact that we suddenly know how it behaves does not change nature's behavior. This tacit assumption almost certainly fails with markets if the discovery is made public. There are a hoard of economists out there who would trample on each other for a better predictive model of markets, which may earn them the Nobel Prize. If indeed such a model is ever developed that can predict the markets well (not only in normal times but also shortly before market crashes) it will spell its own doom. In response to this new model, the behavior of the markets will change sufficiently to counter the prediction and render it useless. The only way such a model remains successful is by not making it public, and guarding it as a trade secret. That's how the likes of Simons and Sornette succeed, while most others eventually fail. Simons and Sornette never reveal how exactly they predict markets using physics. The author could have written a chapter (or several chapters) about this, but he did not.
Finally, the worst part of this book is about the inaccuracies it contains about who did what. Most of these are physics related (quite strangely since the author is supposed to know that), and not about the main topic of the book. For that reason, maybe they are forgivable. For example, the author implies that the gauge theory provides us a way of translating vectors from one point of curved space-time to another. While we physicists know how that should be done, translating points in curved space-time has very little to do with gauge theories. The author later corrects himself by acknowledging that the gauge theories were something else altogether and correctly credits Yang and Mills for discovering them in 1953. Never mentioned in the book is the fact that the first gauge theory even predates Yang and Mills, all the way back to 1879. It is none other than Maxwell's classical electrodynamics, even though Maxwell himself never used that term.
So in summary, if you know very little about quantitative market prediction, I highly recommend the book, you will learn things from this book: four stars. If you have some knowledge about it, then you will not get much out of the book except a few names and places in history, not all of which are correct: two stars. I will average the two ratings.
on November 28, 2012
Weatherall tells that contrary to what we know, Warren Buffet is not the US best investor. The best one is Jim Simons, a brilliant physicist expert in String Theory who founded the investment firm Renaissance Technologies and its Medallion Fund. Simons returns have far outpaced Buffet's. During the recent financial crisis in 2008 when Buffet incurred a 50% loss, Simons Medallion Fund returned 80%. Other outstanding investors include Ed Thorp, James Doyne Farmer and Norman Packard. What those better-than-Buffet investors have in common is that they are all scientists instead of financial types. They use complex mathematical models to implement profitable short-term trades instead of holding stocks over the long term based on fundamentals like Buffet.
Weatherall develops a philosophy of the scientific method that permeates the whole book. Contrary to Taleb who dogmatically states you can't model anything; so, throw the entire body of modern finance out and just buy insurance (Put options); Weatherall, observes that "The model-building process involves constantly updating your best models and theories in light of new evidence."
Weatherall starts the history of modern finance with the French mathematician Louis Bachelier and his revolutionary paper "Theorie de la Speculation" published in 1900. Weatherall states: "In a just world, Bachelier would be to finance what Newton is to physics." Indeed, Bachelier was the first to figure that stock prices captured all information and moved randomly. He explained the related random walk of stock prices. He was a pioneer in applying probability theory to financial markets. He specified the Efficient Market Hypothesis without naming it. The latter will be articulated by Eugene Fama in 1965. Bachelier also innovated an option pricing model based on the arbitrage free principle he also developed. The related Black Scholes option model will be developed much later in 1973. Paul Samuelson uncovered Bachelier's paper in 1955 and was stunned. Bachelier had figured out the mathematics of financial markets that Samuelson was working on at the time. Thus, Bachelier was over half a century ahead of his time.
Next, Weatherall introduces Maury Osborne, an American astrophysicist who will make a key improvement to Bachelier's theory in his seminal 1959 paper "Brownian Motion in the Stock Market." Osborne uncovered that stock price movements follow a log-Normal distribution instead of a Normal distribution as Bachelier advanced. It is stock returns that follow a Normal distribution. This represented a critical improvement over Bachelier's initial theory.
Weatherall, next moves on to Benoit Mandelbrot, a French mathematician, who developed fractal geometry. He uncovered that stock price returns are wilder than the Normal distribution suggests. They are better captured by distributions with fatter tails denoting a higher frequency of extreme events. But, Mandelbrot's work will be rejected because finance theory already developed a large body of useful models based on Osborne's assertion that stock returns follow a Normal distribution. And, Mandelbrot did not offer any pragmatic model alternative. If you want to study Mandelbrot's work further, check out his The Misbehavior of Markets.
Next in chapter 4, we meet three star mathematicians including Ed Thorp, Claude Shannon (inventor of Information Theory) and John Kelly (the Kelly criterion). This chapter is a summary of the excellent book Fortune's Formula: The Untold Story of the Scientific Betting System That Beat the Casinos and Wall Street. Thorp, with assistance from Shannon and Kelly, will develop innovative methods on optimizing strategies at Black Jack by combining his new card-counting method with the Kelly criterion that tells when a player has a probabilistic advantage over the house. Next, Thorp makes a fortune by applying the Kelly criterion to financial markets. He develops a computer driven option pricing model and the related "delta hedging strategy" that entails selling warrants short and buying the related stock. Thorp is another better-than-Buffet investor. Either through a hedge fund or privately, Thorp recorded 20% return per year for 45 years and is still doing it. In 2008, one of his bad years, he still made 18% at the same time that Buffet was experiencing a 50% loss.
Chapter 5 covers the story of the Black Scholes option model developed in 1973 and its main protagonists: the physicist Fischer Black, the economists Myron Scholes and Robert Merton. This chapter is a summary of another great book: Fischer Black and the Revolutionary Idea of Finance. Jack Treynor introduced Black to CAPM in 1968. In 1969, Black ties CAPM and arbitrage free considerations to develop option pricing. Scholes joins Black in resolving the advanced math equations to put together the Black Scholes model published in 1973. Robert Merton develops the same model independently at nearly the same time. Scholes and Merton will receive the Nobel prize in economics for it. Black would have too, but he passed away several years before his colleagues received it.
The same chapter 5 outlines why physicists and mathematicians have gravitated to Wall Street. In earlier times, the main career outlet was the Government such as the Department of Defense (German code cracking and Manhattan Project during WWII, Cold War, Game theory), NASA (race to put the first man on the moon). But, after 1969 when Neil Armstrong became the first man to step on the surface of the moon, the urgency for such endeavors evaporated. And, the job market for physicists collapsed. The end of the Cold War also depressed this job market. In 1984, Black leaves academia for Goldman Sachs. He is one of the first and most notorious quant on Wall Street. Crowds of them will soon follow.
The next chapter covers the intriguing "The Prediction Company" an investment company co-founded by two physicists: James Doyne Farmer and Norman Packard. At first, Farmer and Packard have fun improving upon the roulette prediction that Thorp and Shannon had developed years earlier. Farmer and Packard will translate their roulette calculations into major contributions to Chaos Theory. They co-found The Prediction Company in 1991 that will be soon acquired by O'Connor, a hedge fund. The latter will be purchased by Swiss Bank Corp. But, The Prediction Company will operate as an independent subsidiary. Farmer and Packard will throw everything they know at the financial markets including Chaos theory, statistical arbitrage with genetic algorithms, and Mandelbrot concepts such as "wild" randomness and fat tails. They will develop different models and look for consensus between their valuations before implementing trades. And, they will become very successful investors.
The successes of Jim Simmons, Ed Thorp, Farmer and Packard leads Weatherall to an interesting take on the Efficient Market Hypothesis (EMH). For the markets to be efficient, one investor has to conduct a trade at anyone time so the market price fully reflects all information. This first trader reaps the gains and renders the market efficient for the rest of us. And, all the mentioned investors had this uncanny ability to be this first trader over many years. This suggests that the market is somewhat inefficient. But, the hurdle rate to reap profits from inefficiencies is extremely high. You have to beat Simmons, Thorp and company to be the first investor to capture the inefficiency.
The next chapter is about Didier Sornette, originally a geophysicist turned polymath with a wide range of expertise including economics and finance. He is the world expert on predicting extreme events ranging from earthquakes, tectonic plate movements, and even stock market crashes. For him all those rare catastrophic events leave a forewarning signature in the data consisting in an acceleration (log-periodic pattern) of smaller events leading to the eventual catastrophically larger event. Through his diagnosing those log-periodic patterns, he perfectly predicted the stock market crash of October 1997 and made a 400% return by buying cheap way-out-of-the money Puts on stock indexes. With his log-periodic patterns, he also predicted the dot-com crash in early 2000 and the financial crisis crash of September 2008. So, contrary to Taleb Sornette suggests that Black Swans are sometimes predictable. If you are interested in his work check out his Why Stock Markets Crash: Critical Events in Complex Financial Systems. This is not an easy read. However, Taleb himself gives it a 5 star rating.
In the conclusion Weatherall defends physicists' influence on finance when it is often viewed as nefarious. He takes on behavioral economists who dismiss any quantitative models suggesting they can't capture the complexity of humans. Weatherall rebutts that a better understanding of individual response (Weber-Fechner law) contributed to Osborne's improvement in modeling of stock prices. Also, Didier Sornette incorporated herding behavior in modeling occurrence of financial calamities. Thus, the two fields of behavioral economics and physics are complementary. Next, he addresses Taleb's take that we should throw all models away because they can't anticipate rare events. Weatherall thinks this nihilist position is misguided. Sure, models will never be all prescient. But, following the evolution he documents throughout this book, models are constantly improving. Those improvements increase our understanding of our financial environment. Didier Sornette's work has improved our understanding of the occurrence of rare events. Is there any merit in burning Sornette's work? No. The third criticism is that the physicists were fully responsible for the 2008 financial crisis with their toxic products (CDOs, CDS, MBS) that no one understood including themselves. Weatherall argues the financial crisis was due to institutions using models while not exercising scientific judgment and misunderstanding risk. Renaissance Technologies with the best scientists came out of the financial crisis unscathed. "Renaissance shows that mathematical sophistication is the remedy not the disease... The people charged with running the world's economies should be as good as Renaissance."
I come at this review as an occasional worker in the financial world, a former physicist and a larval futures trader.
The good: the author has some excellent historical material on Bachelier, MFM Osborne and Ed Thorp, who are (mostly) unrecognized giants in the field. I learned a few things, and think the author had some real insights into the contributions made by these men. Frankly, I'd have bought the book for the Thorp and Osborne anecdotes. Someone really needs to do an authorized biography of Thorp, and one of Osborne would be pretty neat as well. Some of the material on Mandelbrot and the prediction company guys was also amusing, though I have always considered these folks overrated. This book is extremely well written, and despite the problems I had with it, I found myself enjoying the reading.
The bad: The subjects of this book are not all people a working practitioner of finance would have chosen. Most of subjects of the book are *known.* Many practitioners of finance (and physics) are only famous because they like publicity and talking to journalists, or because there is somehow a popular book associated with them. I mentioned Mandelbrot and the prediction company guys above: these are accomplished, interesting and talented men. Do they belong in the same league as Ed Thorp or MFM Osborne? I think they'd agree the answer to this question is "no." I've read most of the popular books the author used as raw source material, so most of this book wasn't new. He did reach out to some of the protagonists, and managed to dig up a few things I wasn't familiar with, but the meat of this book exists in several other books out there. Not that there is anything wrong with that; it summarizes about a dozen other books, and does so with considerable style. But if you already know about this sort of thing, you're only getting a few new Thorp and Osborne stories.
I'm not sure I agree with the author's prescription at the end of the book, but new ideas are presently urgently needed, so I'll make supportive noises at all new ideas whether I agree with them or not. For a popular book on this subject, a subject which is the source of much hysteria and popular caterwauling, it isn't half bad. I'd suggest it to the layperson, and short it for the practitioner.
on March 21, 2013
Reading "The Physics of Wall Street" is like reading Cliff Notes for the following books:
1) "Against The Gods" by Peter Bernstein
2) "The Quants" by Scott Paterson
3) "The Predictors" by Thomas Bass
4) "Ubiquity" by Mark Buchanan
5) "Fortunes Formula" by William Poundstone
There is little, if anything, actually new in this book, either in terms of ideas or facts. These stories have all been told before. Furthermore, the author "cops out" after making several strong claims - for example, he writes that the individuals behind The Prediction Company "revolutionized" finance but then admits that he has no idea how they've performed since they set up their company. If no one knows what they are doing or how they are performing, how could they have revolutionized anything? Later on, he talks about the efforts by Eric Weinstein and Pia Malaney to apply gauge theory to solve the economic problem of indexing (specifically indexing inflation), and assures us how innovative this approach is, but then doesn't explain why it's innovative or whether it actually has solved any problems. Where's the beef?
If this is the first book you read about quantitative finance and the intersection between finance and physics, it provides a satisfactory summary - the author is a very capable writer. However, there are many other books (including the ones listed above) that go into more depth and are much more informative then this. If you're interested in this topic, this book can be a starting point but it shouldn't be the end.
IN 1900, a French mathematics student by the name of Louis Bachelier submitted a revolutionary PhD thesis to his committee. Starting with no training in economics, but a solid foundation in probability and statistics theory, he constructed a model of how the prices of a security changed over time. He independently came up with what would later be known as the Efficient Market Hypothesis, and assumed (incorrectly, as it turned out) that changes in prices would be normally distributed over time, and from this he developed a general model that could be used to compute and price risk. This should have started a revolution in finance, and would have if not for the fact that the French mathematics establishment of that time was not particularly interested in applied mathematics. They were concerned mainly with formalism- the structure of mathematics itself- and looked upon even mathematical physics as, well, vulgar. If not for the fact that Bachelier's thesis was supervised by the great Henri Poincaré, it is doubtful his thesis would have been accepted at all. But it was- barely- and then it was promptly forgotten for over half a century, until Bachelier's work was rediscovered by economist Leonard Savage.
Ten years after Savage rediscovered Bachelier's work another advance in the theory of option pricing came from out in left field- this time, from a physicist by the name of Maury Osbourne working in the Naval Research Laboratories. Starting with no particular education in economics, he, too, came up with an brilliant, original model, this time based on the theory of Brownian Motion. Around the same time, a mathematician by the name of Benoit Mandlebrot working at IBM Research was thinking about certain problems of measurability and patterns in nature, and noticed that certain natural phenomena seemed to have patterns that showed up at every scale. The same periodicity seen at the scale of, say, a mile, also showed up at the scale of a foot, an inch, or even a millionth of an inch. The same sort of patterns could also be seen at different time scales, too, and if you're an economist looking at the changes in the price of some commodity, you're very interested in time series analysis and patterns.
Also around that time, a mathematician named Edward Thorpe had come up with a system to beat the odds in Las Vegas by exploiting his knowledge of probability theory, which led him to a general thoery of pricing risk. and a young radical and mathematics grad student by the name of Fisher Black was being tossed out of the PhD program at Harvard for lack of focus and spending too much time on the picket line and in jail cells. Black left academia to work in industry, and it was there he discovered CPAM- the Capital Asset Pricing Model. The former intellectual dilettante was fascinated by the idea of formalizing risk and randomness, and that led him back to academia, and eventually to a partnership with another fresh PhD by the name of Myron Scholes. Working together they came up with what came to be called Black-Scholes Option Pricing Theory. It was very similar in its essence to Bachelier's model, with a few critical improvements; for one thing, It assumed returns, not prices, were normally distributed, and that prices followed a log-normal distribution. (This avoids the problem of negative prices that can happen if you assume that prices follow a normal distribution.)
All of this was mainly of academic interest (except to Thorpe) until the 1980s, when the was an explosion in the market for derivatives on Wall Street. Traders and underwriters who had been dealing with simple things like companies and commodities were suddenly confronted with the need to price complex securities whose price depended on the movement of several different underlying equities. Sophisticated investors had always used options to insure against excessive risk, but now portfolio managers were wondering if there might not be a way to combine several different kinds of securities to create a contract that would always yield a positive return whether the market went up- or down. And to do this they needed mathematics that were a lot more sophisticated than what they'd been used to. They needed something like Black-Scholes (and later, Black-Scholes-Merton) option pricing theory.
Pretty soon, the big banks and brokerages were starting to raid math and physics departments for mathematicians who were familiar with the kinds of sophisticated models that were needed to model risk and construct complex hedges. A generation of brilliant minds used to dealing with the complexities of quantum theory- but without any actual background in economics- were making big money on Wall Street. Scholes and Robert Merton attracted a billion dollars in capital for their investment firm, Long Term Capital Management (LTCM). Unfortunately for a number of these mathematicians and physicists, the rules on economics remained inflexible, and one of the most important is that there's always more risk in the marketplace than any one investor can afford to hedge against. When Russian and Asian defaults triggered a massive collapse in security prices, it brought down LTCM (and a number of other sophisticated hedge funds) with it.
There's a lot more to this story, and many more players. Familiar names like Naheem Talib, and less familiar ones like Herman Weyl figure in a number of the stories. There's the whole problem of Social Security solvency, and the political stories behind the economics. What makes this book work is that author Weatherall is both a skilled enough mathematician and physicist to understand the math and the system dynamics, and at the same time a good enough teacher and writer to help the non-specialist understand why it is that equity prices would fit a log-normal distribution. This is not breezy reading, but it's not full of math, either. There's actually precious little math and just a few clear graphs that explain the concepts Weatherall is trying to convey to the reader. If you're curious about how modern hedge funds work, or where these mathematical models came from, or the factors that were behind the great market collapse of 1997, you'll find this an absolutely captivating read.
on June 28, 2013
I realize that a title 'The Mathematics of Wall Street" would not attract the desired readership, but it's still irritating (to me as a mathematician) to see mathematics being called physics. The book seeks to trace the history (over the last hundred years) of some of the mathematics relevant to finance. But, in a common modern style of writing, it relies on stories about individuals' lives with only rather superficial verbal description of the intellectual content of their ideas. As one extreme, a whole chapter seems built around the notion that "gauge theory can be used to solve economic problems", but there's no indication whatsoever to tell us what that actually means. This style and some of the content is similar to the recent Pricing the Future: Finance, Physics, and the 300-year Journey to the Black-Scholes Equation, which contains more of the pre-20th century history. My own hobby of reviewing such "popular science" style books makes me an atypical reader, in that many of these individuals (Bachelier, Mandlebrot, Thorp, Black and Scholes) have featured with similar stories in other books, so only a few details about those individuals struck me as novel.
Two positive features were the accounts of less well known individuals (Maury Osborne, James Farmer and Norman Packard, Eric Weinstein and Pia Malaney), and the scholarly end notes and references. And of course this style of writing is undemanding to read.
Aside from being over-credulous about recent ideas -- the ability of Sornette-type models to predict earthquakes or financial crises, or the relevance of gauge theory -- there is nothing bad about this book. But it just doesn't have any coherent theme. The whole point of mathematics is that a given piece of math may apply to different things. Saying that theoretical physics uses mathematics and quantitative finance uses mathematics, and these mathematical techniques sometimes overlap, is true but trite. The claim is made that insights from physics (rather than from the underlying math) have had noteworthy impact on finance and economics, but the author hardly even tries to justify this claim.
Bottom line: if you're interested in brief biographies this book is fine; if you're interested in ideas about quantitative finance then there are many better books out there, for instance Fortune's Formula: The Untold Story of the Scientific Betting System That Beat the Casinos and Wall Street and Red-Blooded Risk: The Secret History of Wall Street.
This book is an intellectual Odyssey recounting how some brilliant and unorthodox thinkers have in the last 100 years managed to apply the methodology of mathematics and physics to economics and finance, and in the process revolutionized the capital markets. Reading it I was reminded of Eugene Wigner, a famous theoretical physicist, who wrote an essay entitled " The Unreasonable Effectiveness of Mathematics in the Natural Sciences", which marveled at how accurate mathematics was in describing the laws and behavior of the Universe. As this book demonstrates, it is also amazing at how applicable math is in understanding the extraordinarily complex set of human interactions which make up the market economy.
I really enjoyed this book, which begins with the application of Brownian motion to stock prices and includes fractal geometry as an explanation for highly unlikely events, chaos theory as the foundation for evaluating very short term trading patterns, and the physics of ruptures to predict the drastic events associated with bursting financial bubbles. All these and other interesting scientific and mathematical concepts are presented by the author in a clear, concise manner which is a tribute to the skills and strengths he brings to the task. In another's hands this could have been a very tough book to get through.
Just as interesting are the stories of the people who have imposed this scientific superstructure on what appeared to be a market governed by random behavior. All obviously brilliant, that is not what is so striking about them. Rather is is the maverick,almost renegade, individualistic streaks that defined them and which enabled them to make ground breaking discoveries that really held me in awe. In today's world we see so many specialists who concentrate on narrower and narrower fields. To be exposed to polymaths who can think productively about so many different disciplines and ideas is truly refreshing and encouraging.
The book is a little choppy in structure, a function of the amount of information presented and its relative brevity, and I found the author's tendency to skip around in time a little distracting. Also, while there are no complicated equations, some knowledge of math will make the read more enjoyable, but I really cannot see someone who doesn't like math even considering this book, so that advisement may be academic.
Now in the interest of full disclosure I have a graduate degree in Nuclear Engineering and worked as a trader on Wall Street for several years, and therefore this book was truly tailor made for my interests, and it did not disappoint. However,if you are one of those people who think Wall Street is filled with greedy dastards [and that is not a spelling error]who knowingly engage in nefarious activities to cheat the little [or not so little] guy just to make obscene amounts of money, this book may be an affront to you and you will probably resist one of its conclusion- that financial upheavals like the 2008 market crash were not caused by criminal intent but a failure of the mathematical models. More accurately, it was a misuse of the models which seemed to guarantee that risk was minimized when in fact it was not. Now that does not alleviate the pain which resulted from the meltdown, but it does explain it as an intellectual, not moral failure. Some people will not want to hear that. They probably shouldn't buy this book.
In fact this whole book is an argument for why physics and math should be employed in the service of understanding financial markets and the economy, an opinion many rejected after 2008, blaming them for magnifying the meltdown because of their contribution to the creation of complex derivatives. The author does a good job of addressing this concern, and his final suggestion is that a concerted effort should be made to ensure that the regulatory bodies are at least as proficient as the bankers and brokers in understanding how science and math apply to the financial world so as to prevent another 2008. While good in theory, it has proven to be the rule that the profit driven private sector always seems at least one step ahead of the government in terms of cutting edge ideas, and hoping that a New Manhattan Project can rectify that in the financial markets is truly betting on a long shot. But as you will discover in this book, the extremely unlikely happens more often than you would imagine!
So I recommend this book for all of you with an open mind and an intellectual curiosity about this subject who would like to get a comprehensive though somewhat cursory, entertaining overview of how some very brilliant people have succeeded in plumbing the depths of economics and finance using the tools of mathematics and physics. The genie has been let out of the bottle and is not going to go back in, so it behooves us to understand the new world that has been created. Those who rail against the financial revolution are Luddites who have no chance of returning to simpler times. This is a great book with which to educate yourself. And you will enjoy it too.
This is a great book by a good writer, bursting with ideas, science, mathematics, biographies of great thinkers, and lots of things that I feel I should have known about before. It tells the story of how scientists and mathematicians came to Wall Street, analyzed boatloads of stock price data, and quantified it (thus they were called quants), creating models that forever changed the way people and their computers invest. That sounds like a dry subject, but Weatherall makes it fascinating, with the stories of the people who made it happen.
I had never heard of Claude Shannon, the founder of information theory, which became a whole new science. I had heard about the random walk theory of stock prices, but not the back story about the origins of the theory, and how the author of that famous book neglected to acknowledge his sources. The science of complex systems and chaos theory are here too. Each chapter includes the stories of scientists, how they grew into their fields, how they faced long odds, and how they came to make their signature contributions to investing. The writing is very approachable, not technical. People without a math or science background will have no difficulty reading and understanding this story.
This book does not include a fool-proof formula for your personal investing success. It did help me to understand the place of mathematical models in investing, their strengths and weaknesses, and more importantly, the fact that all models can break down under certain circumstances. The author also explains clearly and effectively how the banking crisis of 2007-8 evolved, how our government (and other governments too) failed to fix the fundamental problems, and therefore how the threat of another crisis is ever present. Government regulations pushed through in the last few years are outdated fixes for yesterday's problems. Weatherall does have a solution, but it is unlikely that enough people will pay attention. I am glad that I read this fine book, and I recommend it to everyone who cares about the economy, the markets, and our financial future.
on December 27, 2013
This very readable book might better be called "The Physicists of Wall Street," as it tells about the geniuses who have given us improved understanding of the casino called "the stock market." French physicist Louis Bachelier over a century ago modeled the market as being a random walk, a drunken lurching, with steps that followed a normal [Gaussian] distribution. The equations and implications implications he deduced went nearly unnoticed for five decades, when the great M.I.T. economist Paul Samuelson was alerted to them, only to find that much of his own recent work had been scooped by Bachelier, whom Weatherall considers the Isaac Newton of economics.
Who cares? Those who invest daringly in the market, beyond my own favorite, the "buy and hold" strategy, which has worked well for Warren Buffett. Options, futures, warrants...these derivatives based on stock prices are much more sensitive than the stocks themselves to changes in the environment and changes in the traders' world-views. Fortunes have been made and fortunes lost, some of the latter due to the bubbles that the fizz of the physicists helped create. The normal distribution was not quite right. Physicist Maury Osborne found the log-normal made more sense: it never went negative, fit the data better, had larger [and more accurate] probabilities for some extreme events. Eventually, Benoit Mandelbrot showed that distributions that gave even larger probabilities for extreme events [had longer, fatter "tails'] were needed and still could under-predict market collapses. Nassim Taleb in "The Black Swan" and "Antifragile" maintained that the truly unusual cannot be predicted, only hedged against.
Some physicists in the market have become billionaires, so they know things most of us do not. One strategy has been to use computers and sophisticated algorithms, usually closely held secrets, to move a bit faster than the market to get in ahead of the ups and out ahead of the downs. This works when in the normal trading regime. Clever hedging with stocks and warrants etc. can also deliver nice returns in normal times. There may be clues that warn of impending crises, as physicist Didier Sornette has shown, but most of us may be wise to follow Prof. Taleb's injunction to put the bulk of our investments in safe, conventional alternatives, speculating with a small fraction...and generally betting that disaster has been under-estimated.
Economists tend to be skeptical of physicists in their playground. Some humility is appropriate on both sides. Still, it was Nobel-prize-winning economists who rode Long-Term Capital Management into bankruptcy, apparently partly due to relying on the normal distribution, rather than something a little more complicated and closer to reality.
Weatherall's book has extensive notes and references and a couple of figures, but no equations. The stories are well-told, with a mix of interesting personal and technical information. Lots can be learned, just don't bet the farm.
I really liked this book, but I am a retired physicist. We transcend humility.
It is often said there were two great revolutions in physical science in the 20th century - quantum mechanics and relativity - but actually there were three. The discovery and growth of nonlinear dynamical theory, including chaos and fractals, cellular automata and catastrophe theory, are at least equally important. In most cases these methods do not allow for exact concrete predictions, but they have greatly advanced our qualitative understanding of complex natural phenomena. One such area of natural phenomena is human financial markets.
This book, which is a work of recent history and popular science journalism rather than a textbook, follows the fascinating story how mathematical analysis overall and in particular the science of complexity made its way outside the physical sciences and into finance and other areas of public discourse. Included is Mandelstam's discovery that the statistics of market prices are not Gaussian as had been assumed for more than a century, but fractal, with inevitable large fluctuations; he should have won the Nobel Prize in economics for this but was too much of an outsider to be considered. The author renders it all as a human saga of adventures and personalities including such riotous episodes as the Los Alamos group who attempted to beat the blackjack tables at Las Vegas, and the story of physicist Jim Simons, probably the most successful and least known investor in the history of the world.
Of course attempting to use the latest ideas of physics to make a fortune in the markets is a sexy subject, but complexity theory also explains many other mysteries, such as the twisted rings of Saturn and the response of our weather to global warming. Weatherall has a mathematical background and is well prepared to tell the story, although his narrative is more anecdotal than systematic and his choice of material is uneven.
Anyone who becomes enthralled by the story of math, physics and complexity in the financial realm with also enjoy "The Black Swan" by Nassim Taleb, "Beat the Market" by Edward Thorp, "Misbehavior of Markets" by Benoit Mandelstam, and "A New Kind of Science" by Stephen Wolfram, all of which are accessible to the non-specialist. Another well written book with many insights into everyday life - such as the meaning of Zipf's Law and the reason why 'the 1%' make 90% of the money - is "Fractals, Chaos, Power Laws" by Manfred Schroeder.
Weatherall's book is an excellent contribution and all investors would be wise to read it. Recommended.