Editor's note: The following column is the second part of an ongoing series of articles by Aaron Brown examining the claims made in The Physics of Wall Street: A Brief History of Predicting the Unpredictable
, a new book by James Owen Weatherall.
Click here to read Part 1.
Last week I started an account of James Weatherall’s new book, The Physics of Wall Street
. This is not a review of that book. Rather I’m taking advantage of the errors in the book, errors common when quantitative people without experience at risk-taking begin thinking about finance, to clarify the principles of modern quantitative finance. Part I
dealt with Weatherall’s thesis that physicists invented the modern financial system. This week I turn my attention to a consequence of that mistaken claim.
Most people who approach finance without training in finance or economics begin by focusing on the statistical properties of historical recorded prices. This can be as naïve as, “Boy, if I had known what this price was going to do, I could have been rich,” or more sophisticated, such as, “I’m sure I can detect some subtle patterns in the historical data that will give me insight into finance.”
While this “random walk” research is important in finance, it is by no means the whole field. Historical recorded prices, whether transactions or estimates, are quite different from the actual future transaction prices that matter to actual financial decisions. Many of the interesting problems in finance arise only when you consider real transactions, not paper trading assuming complete information, zero market impact, and zero transaction costs. Moreover, financial prices are the result of real economic forces. Treating them as random can lead to some useful insights, but to rebuild the global financial system, it is essential to account for the links between financial prices and real activity; you cannot treat price movements as uncaused.
In Weatherall’s world, the only goal of finance is to guess future price movements. That reduces both the intellectual interest and social utility of finance to the level of figuring out how to play the lottery. Only someone of extraordinary arrogance could believe that generations of researchers and practitioners—not to mention an appreciable slice of the economy—was engaged in such pointless game playing, on the basis of reading one (admittedly excellent) book on the history of finance and ignoring all the parts that he didn’t want to believe.
Guessing future price movements based on statistical models does have a place in finance, but only at extremes of scale. High-frequency traders can treat order flow as random because they operate at a speed at which economic news transmission is negligible. Long-term diversified investors can take advantage of regularities documented in very large portfolios held over very long periods of time, because on a large enough scale you can assume the deterministic components average out (maybe, anyway, that is more an article of faith than a proposition falsifiable at a human scale). But almost all of finance is done at intermediate scales where both economics and market structure matter. And even at the extremes, the simple random-walk research is not directly applicable. At small scales, price is not well defined. At large scales there is not enough historical evidence to define meaningful probability distributions.
This narrow conception of finance causes Weatherall to miss the tremendous intellectual importance of the random-walk model. Treating price changes as random variables freed researchers from worrying about fundamental economic valuation. In turn, that allowed people to study returns of different securities and returns at different time periods as indistinguishable elements which were realizations of abstract probability distributions. Despite the obvious fictions in that process, studying the abstract distribution of price changes, instead of the levels of actual prices, turned out to be enormously productive.
An even more important insight was the rejection of the old saying, “Difference of opinion is what makes a horse race.” Earlier models assumed that if I sell you a share of stock for $40, I must believe the share is worth $40 or less, you must believe it’s worth $40 or more. While that’s probably true most of the time, it’s useless for scientific investigation because you can explain any transaction by invoking disagreement. If you can explain anything, you explain nothing. Assuming that investors agreed on the statistical properties of security returns and transacted for portfolio reasons allowed people to build testable models of rational markets.
Physics did something similar in the development of thermodynamics. Treating the motion of individual gas molecules as random led to simple mathematical formulae that were valid at the macroscopic level, and also to deep insights about the nature of reality. But physicists did not stop all other research in order to try to guess the future motion of individual gas molecules. That misses the point entirely. Physicists knew that physical laws, not random number generators, were responsible for the motion of gas molecules, and finance researchers knew it was economic laws, not random number generators, were responsible security price changes. But in both cases, the random-walk assumption led to important progress.
The random-walk model is sometimes described as treating the financial system as a casino. In fact, there is deep insight about finance that springs, both historically and logically, from the study of casinos. Not the theoretical casinos of probability textbooks, but the real human institutions. I’ll discuss that next week in, “To see the world in a grain of sand, to see the financial system in a roulette wheel.”
No positions in stocks mentioned.
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