Minggu, 13 Januari 2013

Ebook The Physics of Wall Street: A Brief History of Predicting the Unpredictable, by James Owen Weatherall

Ebook The Physics of Wall Street: A Brief History of Predicting the Unpredictable, by James Owen Weatherall

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The Physics of Wall Street: A Brief History of Predicting the Unpredictable, by James Owen Weatherall

The Physics of Wall Street: A Brief History of Predicting the Unpredictable, by James Owen Weatherall


The Physics of Wall Street: A Brief History of Predicting the Unpredictable, by James Owen Weatherall


Ebook The Physics of Wall Street: A Brief History of Predicting the Unpredictable, by James Owen Weatherall

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The Physics of Wall Street: A Brief History of Predicting the Unpredictable, by James Owen Weatherall

Amazon.com Review

Q&A with James Owen Weatherall Q. What is The Physics of Wall Street all about? A. Over the past few years, we've heard a lot about a new kind of Wall Street elite known as "quants." These are often physicists and mathematicians who have moved to finance and brought radically new ideas along with them. This book is an attempt to understand these quants and the mathematical models they use to predict market behavior. It's two parts history and one part argument: I tell the surprisingly fun story of how physicists and their ideas made it to Wall Street in the first place, and along the way I argue that this history reveals something important about how we should think about the models and practices they have introduced--especially in light of the 2007-2008 financial crisis. Q. You say the history is surprisingly fun. Can you give an example? A. The physicists and mathematicians I write about in the book are (or were) very smart, creative people who put their scientific training to use in surprising new ways. Their stories are fascinating. For instance, Edward Thorp, who invented the modern quantitative hedge fund, was also the first person to prove that card counting could be used to reliably get an edge in blackjack. He spent a good amount of time working the card tables in Las Vegas. And Norman Packard and Doyne Farmer, who started a pioneering financial services firm in the early 1990s, spent their graduate school years at UC Santa Cruz inventing the new science of chaos theory while trying to build a computer to beat the odds in roulette--the profits from which were intended to start a yippie commune in the Pacific Northwest. Q. What surprised you most about the history you uncovered? A. One thing that surprised me was that derivatives contracts such as options, futures, and swaps, which are often discussed as though they were a troubling new innovation, have actually been around for thousands of years. For example, scientists have found cuneiform tablets containing records of futures traded by ancient Sumerians. Even the idea of using mathematical methods to price options is quite old. I pick up the story in 1900, with the visionary work of a French physicist named Louis Bachelier, but some strands go back further, to the mid-nineteenth century. Plus, there are some striking historical connections in the book. For instance, I explain the relationship between the invention of nylon and the development of the atomic bomb--and how both influenced at least one physicist's to switch to a financial career. And I tell the story of how the space race and the Vietnam War were partly responsible for many physicists moving to Wall Street banks in the 1980s. Q. What can this history teach us about models used in finance? A. If you look at how the physicists and mathematicians who came up with the earliest financial models thought about what they were doing, the role of simplifying assumptions and idealizations becomes very clear. The goal was to get a toehold on some very hard problems, and not to come up with a final, overarching theory of financial markets. Making simplified assumptions can lead to the solution of a problem that you otherwise couldn’t solve--but that solution is only going to be a reliable guide to how the world works when the assumptions you’ve made are approximately true. The important question, and the one that physicists are always trained to ask, is when do your assumptions fail and what happens when they do? I don’t think the importance of this question has been recognized as widely as it should be among the traders who rely on these models. Q. At the end of the book, you describe an "Economic Manhattan Project." What would that be like? A. The Economic Manhattan Project was proposed in 2008 by the mathematical physicist and hedge fund manager Eric Weinstein. The idea is that economic and financial security--that is, regulating the economy to avoid future calamities--should be at the very top of our agenda. Yet the resources we devote to physical security, to military technology and defense, far outstrip what we spend on developing better economic theories. In the past, America has set goals--for the original Manhattan Project, the race to the moon, and others--when we have funneled resources into serious innovation. And whenever we have done so, we have succeeded in accomplishing great things. I think it is time to make a similar kind of commitment to developing the next generation of economic models, with the goal of finding radical new ideas to make the economy safer and more robust. Q. You're a philosophy professor. Why did you write a book about finance? A. The short answer is simply that I find the history and the ideas fascinating. I have a Ph.D. in physics and I like thinking about how physics can be applied to novel problems. The longer answer is that the issues in this book aren't so far removed from philosophy. Philosophers spend a lot of time thinking about what we can know about the world and how to deal with fundamental uncertainty. Philosophy has a reputation for being abstract and distant from everyday concerns. And sometimes it is. But when it comes to mathematical models, philosophical issues really matter for how we make important economic and financial decisions--decisions that have significant real-world ramifications. And for me, at least, the most interesting and important philosophical questions are those that we face as practicing scientists and policymakers--and even as investors.

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From Booklist

Wall Street has long attracted talented business-school graduates; only in recent years has it also drawn analysts with doctorates in physics, mathematics, and statistics. That change is the focus of this fascinating history by a young University of California, Irvine, professor. Weatherall’s narrative mixes familiar names (Blaise Pascal, Pierre de Fermat, Paul Samuelson, Fischer Black, Myron Scholes) with more obscure figures like Gerolamo Cardano, Louis Bachelier, and Didier Sornette. Many key concepts will be familiar from the financial press: e.g., random walk theory, delta hedging, dynamic hedging, and black box models. Happily, the author has a gift for making complex concepts clear to lay readers. Weatherall understands the temptation to blame the quants for the 2008 market crash but urges that the danger comes when we use ideas from physics, but we stop thinking like physicists. Thinking like physicists means recognizing that every model is based on simplifying assumptions and that model building requires a constant iterative process of testing and improvement. Using that process, Weatherall argues, quants can offer useful insights and tools for both economic policymakers and financial speculators. --Mary Carroll

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Product details

Hardcover: 304 pages

Publisher: Houghton Mifflin Harcourt; First Edition edition (January 2, 2013)

Language: English

ISBN-10: 0547317271

ISBN-13: 978-0547317274

Product Dimensions:

6 x 1.1 x 9 inches

Shipping Weight: 1 pounds (View shipping rates and policies)

Average Customer Review:

4.0 out of 5 stars

126 customer reviews

Amazon Best Sellers Rank:

#352,416 in Books (See Top 100 in Books)

About some of the scientists who went into finance, and some of the ideas they brought to bear on the subject. The book, however, has many problems. One is that a lot of the material is covered at length elsewhere (fortune's formula and the eudaemonic pie come to mind), and the author does not see fit to cite this work. Nor does he cite Mandelbrodt's the misbehavior of markets, despite a considerable portion of the book being devoted to Mandelbrodt's work on finance.Second, the autho's hero worshipping approach is quite annoying - many of the people covered are well-known for their considerable talents in marketing themselves, and the author swallows the pitch hook, line, and sinker. For more on this, check out the low-star reviews of Sornette's 2009 book (and no, Mandelbrodt DID NOT discover fractals - they were studied by Julia before Mandelbrodt was born).Thirdly, the author does not appear to be a practicing financier, since his comments on finance proper are quite shallow.

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.

This book is an intelligent explication about the financial phoenomena. The author so follows several models of important economists, whom have tried to read inner those aspects. Particularly it is interesting as the fractal mathematics had had the possibility to arrive at this level of knowledge, in a better way than the tradition related to the Black-Scholes theorem.Economists as Taleb and Krugman, with mathematicians as Poincaré, Mandelbrot, Lévy, represent the foundaments of a new science which knows the economy in similar way of quantum physics.Quantum mathematics and this new economics must be given by exact axioms, and that will be the next job of mathematics.

Weatherall's book is very timely because it covers one of the least understood aspects of the 2007-2010 financial crisis: the change on Wall Street from hiring well-bred young Ivy Leaguers to hiring mathematicians and physicists. Weatherall's early chapters on the pioneers of quantitative methods in finance are very well done, and he explains clearly the basic issues in applying such methods to finance. The second half of the book, however, becomes a polemic and Weatherall doesn't explain what went wrong in the 2000s except to say that he disagrees with Nicholas Taleb's "Black Swans". In particular, I don't understand how he could write a book on this subject and devote only one sentence to James X. Li's application of copula functions, which were the engine underlying CDOs and were a classic case of work imported from academia to Wall Street - and, furthermore, his sentence is wrong.

This book starts out interesting, as the author discusses the early history of mathematical finance culminating in the success of early hedge fund pioneers such as Thorp. However, the thread is mostly lost in the 2nd half amidst rambling discussions of two physics "applications" (chaos theory to crash prediction, and gauge theory to inflation), which are dubious to say the least. It would have been much more interesting for this reader to learn exactly what it is that most physicists are actually doing on Wall Street now, and how those activities make so darn much money. Why couldn't he track down former employees of Jim Simons, or ultrafast trading algorithm designers, or physicists working as risk modelers at banks, and tell us what they do?

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