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Physics of Wall Street: A Brief History of Predicting the Unpredictable (Anglais) Broché – 4 février 2014

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Descriptions du produit

Revue de presse

"Fascinating history...Happily, the author has a gift for making complex concepts clear to lay readers."  Booklist

"A lively account of physicists in finance...An enjoyable debut appropriate for both specialists and general readers." Kirkus

"Anyone interested in how markets work will appreciate this serious hypothesis."  Publishers Weekly

Biographie de l'auteur

JAMES 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.
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Détails sur le produit

  • Broché: 304 pages
  • Editeur : Mariner Books (4 février 2014)
  • Langue : Anglais
  • ISBN-10: 0544112431
  • ISBN-13: 978-0544112438
  • Dimensions du produit: 1,9 x 13,3 x 20,3 cm
  • Moyenne des commentaires client : 2.0 étoiles sur 5  Voir tous les commentaires (1 commentaire client)
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Couverture | Copyright | Table des matières | Extrait | Index | Quatrième de couverture
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0 internautes sur 1 ont trouvé ce commentaire utile  Par Charles-Antoine de Thibault le 28 mars 2013
Format: Relié Achat vérifié
If you have already a good general knowledge about financial markets, this book will not really teach you much. This book remains too general about the impact of the mathematicians/physicians in financial markets. Also, when I read the part on Torp I really had the impression that I was reading the interview of Torp in the Hedge Funds Market Wizards with different wording.

While I was reading this book I really had the impression that the author's goal was to write a book rather than coming to a point.
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113 internautes sur 116 ont trouvé ce commentaire utile 
A mix bag of good and not so good 13 janvier 2013
Par physics lover - Publié sur
Format: Relié Commentaire client Vine pour produit gratuit ( De quoi s'agit-il? )
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.
86 internautes sur 97 ont trouvé ce commentaire utile 
A great history of the evolution of modern finance 28 novembre 2012
Par Gaetan Lion - Publié sur
Format: Relié Commentaire client Vine pour produit gratuit ( De quoi s'agit-il? )
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."
19 internautes sur 20 ont trouvé ce commentaire utile 
Useful review of the role of some physicists on Wall Street 13 janvier 2013
Par Scott C. Locklin - Publié sur
Format: Relié Commentaire client Vine pour produit gratuit ( De quoi s'agit-il? )
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.
18 internautes sur 20 ont trouvé ce commentaire utile 
A survey of financial history but nothing new here ... 22 mars 2013
Par Michael E. Strupp - Publié sur
Format: Relié
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.
9 internautes sur 10 ont trouvé ce commentaire utile 
A fascinating book for the curious and intelligent reader 8 décembre 2012
Par Michael J. Edelman - Publié sur
Format: Relié Commentaire client Vine pour produit gratuit ( De quoi s'agit-il? )
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.
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