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Reviews
The Physics of Wall Street: A Brief History of Predicting the Unpredictable by James Owen Weatherall
davidsteinsaltz's review against another edition
3.0
Some interesting material, some of it novel, reasonably well explained. The author is a bit too credulous of physicist-bankers' self-promotion.
milandeep's review against another edition
1.0
Warren Buffett bashing is a common past-time of a certain type of people. They like to say, he can't predict market movements, but we can. They are computer geeks, mathematicians and physicists who happen to ditch their own fields of science and want to make bucket loads of money – and very quickly. They jump into finance like greedy monkeys. After failing to predict every disaster, they say - the crisis was partly a failure of mathematical modelling. Have they heard of randomness? May be. Do they know that there is something called uncertainty? They think they can model it. So, did their models predict the coronavirus? Did it predict the Russian invasion of Ukraine? They arbitrage securities in complex trading strategies. When it works, they can make millions or sometimes even billions. When their models fail, the government bails them out to prevent widespread economic collapse.
beets_enjoyer's review against another edition
4.0
Terrific book, if not for the faint of heart (or shy of numbers). While a letdown after reading the true master of this genre, Michael Lewis, I found Weatherall's prose to be serviceable. He does a decent job of making you interested in the fascinating outsiders (like Louis Bachelier and Fischer Black, to name a few) that made the initial leap of faith from math and physics over to investing.
Where Weatherall really shines, though, is when he's explaining the various abstruse concepts that underlie the subject of his book. Random walks, gauge theory and the Kelly criterion are all laid out in gloriously understandable analogies. They might require some background in stats or math for you to understand them perfectly, but not much.
One star is deducted for its heavy-handed and slightly anti-climactic ending chapters. Instead of ending with a big bang, Weatherall instead descends into a whimper of a look at how physics might be used to make better political decisions. His call for a "Manhattan Project" to this end falls flat and ends up fairly unconvincing (and boring).
I was otherwise impressed with this book and would recommend it.
Where Weatherall really shines, though, is when he's explaining the various abstruse concepts that underlie the subject of his book. Random walks, gauge theory and the Kelly criterion are all laid out in gloriously understandable analogies. They might require some background in stats or math for you to understand them perfectly, but not much.
One star is deducted for its heavy-handed and slightly anti-climactic ending chapters. Instead of ending with a big bang, Weatherall instead descends into a whimper of a look at how physics might be used to make better political decisions. His call for a "Manhattan Project" to this end falls flat and ends up fairly unconvincing (and boring).
I was otherwise impressed with this book and would recommend it.
nanometers's review
challenging
informative
medium-paced
3.5
Interesting read on how finance and economics have been influenced and modeled by our greatest mathematicians and physicists, where markets are yet another chaotic system in our world.
fisumlucas's review against another edition
4.0
Apesar do título enganador (o livro não é tanto sobre a Física, mas sobre os físicos - e matemáticos - que contribuíram para Wall Street), é um livro interessante de ser ler. Como físico, adoro especialmente o cope dos economistas a criticar este livro, e isso em si já é suficiente para ser um bom livro.
davidr's review against another edition
5.0
This book is a wonderful introduction to history of predicting stock prices using mathematics and concepts from physics. It is basically a history of pricing models; from the earliest mathematical models to the most modern ones. Of course, the best ones are maintained in secret by some super-secretive investment companies, for good reason. The only way a pricing model can be profitable is it to be better than most others being used.
The author, James Weatherall, has a PhD in physics, and is presently an assistant professor of logic and philosophy of science at the University of California, Irvine. He writes with clarity and an engaging style. His narrative follows a logical path, and does not take big diversions along the way.
Now, many of the subjects of this book are not physics at all, but applied mathematics. For example, the so-called "black box" model does not use any physics, but use purely statistical associations that are discovered algorithmically. Their name stems from the fact that they are opaque; they may make accurate predictions, but they offer no insight into the reasons for their predictions. Hence, it is difficult to judge how much confidence should be given to their results. But, for example, a model that predicts an investment strategy that returns a hundred times the S&P 500 over a fifteen-year period is nothing to be sneezed at.
Some of the models are definitely an application of physics concepts, such as the gauge theory model. I find if fascinating that this arcane physics concept has some practical applications in economics and predictions.
Some people blame these computer models for the disastrous economic downturns and stock market volatility that occur from time to time. While Weatherall sympathizes with this attitude, he wholeheartedly endorses the models, as they are simply tools. Sometimes, the assumptions and limitations of these tools are ignored, with dire consequences.
The author, James Weatherall, has a PhD in physics, and is presently an assistant professor of logic and philosophy of science at the University of California, Irvine. He writes with clarity and an engaging style. His narrative follows a logical path, and does not take big diversions along the way.
Now, many of the subjects of this book are not physics at all, but applied mathematics. For example, the so-called "black box" model does not use any physics, but use purely statistical associations that are discovered algorithmically. Their name stems from the fact that they are opaque; they may make accurate predictions, but they offer no insight into the reasons for their predictions. Hence, it is difficult to judge how much confidence should be given to their results. But, for example, a model that predicts an investment strategy that returns a hundred times the S&P 500 over a fifteen-year period is nothing to be sneezed at.
Some of the models are definitely an application of physics concepts, such as the gauge theory model. I find if fascinating that this arcane physics concept has some practical applications in economics and predictions.
Some people blame these computer models for the disastrous economic downturns and stock market volatility that occur from time to time. While Weatherall sympathizes with this attitude, he wholeheartedly endorses the models, as they are simply tools. Sometimes, the assumptions and limitations of these tools are ignored, with dire consequences.