Customer Reviews The Physics of Wall Street A Brief History of Predicting the Unpredictable
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86 of 97 people found the following review helpful
5 A great history of the evolution of modern finance
By Gaetan Lion 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.