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This year’s prize goes to three economists who made contributions to the pricing of speculative assets such as stocks. Eugene Fama, of the University of Chicago, and the oldest of the three, is best known for his development of the efficient markets hypothesis. Lars Peter Hansen, also of the University of Chicago, and the youngest of the three, for exploring the “boundedness” of market processes, both in theory and in empirical estimation. Robert Shiller, of Yale University, has explored the behavioral underpinnings of price determination, arguing that market prices often over-react to changes in fundamental value.
Fama’s efficient market hypothesis is today a textbook standard. It negates the profitability of “technical analysis.” Market prices reflect all past, publicly-available information, and perhaps even private information, and certainly reflects any potential information in stock market patterns (such as “triple bottom,” said to be a prediction of a “breakout” and a “buy” signal). But, doesn’t the efficient market hypothesis disprove itself, as who, if nobody can profit from buying or selling stocks based on information, impounds information into stock prices? To more precisely say that, at the margin, market prices reflect all past, publicly-available information is almost to admit that there are times when stock prices don’t; i.e., when stock prices are “infra-marginal;” or, when the capital available to those who rationally-value stocks is insufficient for them to bring price to value. In his later years, Fama himself seemed to challenge his earlier work in his collaboration with Kenneth French, with the “three-factor” model. In the three-factor model, small cap stocks and stocks with exceptionally high ratios of market to book value, along with systematic risk, are shown to affect stock prices. To be sure, the three-factor model might reflect an underlying multi-factor model of stock price determination, and have nothing to do with information-efficiency.
Shiller’s work is both more recent and on-going, and part of a broad line of inquiry concerning the impact of psychological factors, even irrationality, on stock prices. Why, for example, do we observe “booms” and “busts” in markets in speculative assets, including real estate as well as stock markets; or, “balloons” or “bubbles,” followed by their “bursting.” Even more so, why is the bursting of a bubble in real estate and in stocks so often followed by a recession, or even by a long period of depressed economic conditions? In some early work, he appeared to challenge the efficient market hypothesis head on, arguing that stock prices were more volatile than could be justified. The Crash of ’87 seemed to validate his argument and instigated concerns for “behavioral foundations” and “market microstructure” and such. Shiller’s book “Irrational Exuberance,” taking off on an expression coined by Alan Greenspan, connected that gyration of the stock market to a long history of stock market behavior. Then came the calamitous collapse of the stock and real estate markets during 2008.
Hansen’s contributions to our understanding of financial markets seems to just be getting started. Beginning with technical issues of econometric estimation, he has moved on to the more philosophical issue of the difference between risk and uncertainty. Risk, we might say, is something measurable. It comes from frequencies of occurrence in repeated trials. With sufficiently many trials, we can estimate risk. Uncertainty comes from not knowing the model out of which are coming the outcomes we observe. In a world that is changing, uncertainty can never be resolved. The question, in prudent decision-making, is robustness, as Hansen puts it in his recent book coauthored with Thomas Sargent. By robustness, I mean surviving what otherwise would be catastrophic. What doesn’t kill you, makes it stronger. But, you have to avoid getting killed.
The contributions of this year’s triplet of economists involve advances in the utilization of data, as well as the development of theory. Fama cut his teeth with the analysis of daily stock market data, involving hundreds of stocks, over long periods of time. For example, he tracked the evolution of stock prices relative to “events” such as increases in dividends. This was the “big data” of his time. Shiller constructed and analyzed very long histories of stock market prices, and – more recently – developed of indices of real estate prices (the Case-Shiller index). Hansen is a developer of “agent models,” in which computer models simulate thousands or even millions of persons organized into so many households and companies. Agent models, like climate models, have to be seeded with “parameters,” and checked against observation and “intuitive validity.” They’re not so much proofs, but explanations. They become evidence when validated against data unknown at the time of their construction.