The Physics of Wall Street: a brief History of Predicting the Unpredictable

particularly important because the problems with these criticisms re-
veal why we should reconsider Weinstein’s proposal.
one of the most prominent arguments against mathematical mod-
eling in finance might be thought of as an argument from psychology 
and human behavior. the idea is that ideas from physics are doomed 
to fail in finance because they treat markets as though they’re com-
posed of things like quarks or pulleys. Physics is fine for billiard balls 
and inclined planes, even for space travel and nuclear reactors, but as 
newton said, it cannot predict the madness of men. this kind of criti-
cism draws heavily on ideas from a field known as behavioral econom-
ics, which attempts to understand economics by drawing on psychol-
ogy and sociology. from this point of view, markets are all about the 
foibles of human beings — they cannot be reduced to the formulas of 
physics and mathematics.
there is nothing wrong with behavioral economics — it is clear 
that a deeper understanding of how individuals interact with one an-
other and with markets is essential to understanding how an economy 
works. But a criticism of mathematical modeling based on behavioral 
economics trades on a misunderstanding.
Using physics as a springboard for new ideas in finance does not 
involve describing people as though they were quarks or pendulums. 
think about how the ideas discussed in this book have made the move 
from physics into financial modeling. Some physicists, like Mandel-
brot and osborne, made progress in understanding markets by sim-
ply drawing on their familiarity with statistics to identify new ways 
of thinking about markets and risk. others, like farmer and Packard, 
used their expertise at extracting information from a noisy source to 
identify local patterns that could be useful for trading. Still others, like 
Black, derman, and Sornette, combined their observations about the 
details of markets in action with theoretical expertise learned in phys-
ics to come up with mathematical expressions that describe how read-
ily observed features of markets (like stock prices and fluctuations) 

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relate to more opaque features (like options prices and oncoming 
crashes). none of these examples involves assuming that investors are 
a bunch of quarks or that firms behave like exploding stars.
there’s a deeper issue here, however. A careful study of human be-
havior is hardly inconsistent with using mathematical models to study 
markets and the economy more broadly. Indeed, psychology, in the 
form of the Weber-fechner law, played an important part at the very 
beginning of mathematical modeling of stock prices: osborne used it 
to explain why stock prices exhibited a log-normal distribution and 
not a normal distribution. More recently, Sornette has shown how ac-
counting for herding effects — another important aspect of human 
psychology, and a mainstay of the behavioral economics community
— can be useful in predicting financial calamity using mathematical 
techniques. In both of these cases, an understanding of psychology has 
played a crucial role in developing and refining mathematical models. 
In general, one should expect studies of psychology and human behav-
ior to be symbiotic with mathematical approaches to economics.
A second kind of criticism — one that has already come up in the 
book — has found its biggest champion in nassim taleb. taleb has 
written an influential book, The Black Swan, which argues that mar-
kets are far too wild to be tamed by physicists. A black swan, you’ll 
recall, is an event that is so unprecedented it is simply impossible to 
predict. Black swans, taleb argues, are what really matter — and yet 
they are precisely what our best mathematical models are unable to 
anticipate. this is a particular problem for financial modeling, taleb 
says. He argues in his book and in many articles that physics lives in a 
world he calls “Mediocristan,” whereas finance lives in “extremistan.” 
the difference is that randomness in Mediocristan is well behaved and 
can be described by normal distributions. In extremistan, normal dis-
tributions are simply misleading. for this reason, he argues, applying 
ideas from physics to finance is a fool’s errand.
on one level, what taleb says is certainly true — and absolutely es-
sential to recognize, especially for people who rely on mathematical 
models to make real-world decisions. We will never be able to predict 
everything that can happen. for this reason, a measure of caution and 
a good helping of common sense are always going to be important 

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Epilogue: Send Physics, Math, and Money! 
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when we try to use models successfully. But recognizing that we will 
never be able to predict everything, and that we shouldn’t assume our 
models reveal some deep truth about what can and cannot occur, is