From Ef cient Markets Theory toBehavioral FinanceRobert J. ShillerAcademic  nance has evolved a long way from the days when the ef cientmarkets theory was widely considered to be proved beyond doubt. Behav-ioral  nance—that is,  nance from a broader social science perspectiveincluding psychology and sociology—is now one of the most vital research pro-grams, and it stands in sharp contradiction to much of ef cient markets theory.The ef cient markets theory reached its height of dominance in academiccircles around the 1970s. At that time, the rational expectations revolution ineconomic theory was in its  rst blush of enthusiasm, a fresh new idea that occupiedthe center of attention. The idea that speculative asset prices such as stock pricesalways incorporate the best information about fundamental values and that priceschange only because of good, sensible information meshed very well with theoret-ical trends of the time. Prominent  nance models of the 1970s related speculativeasset prices to economic fundamentals, using rational expectations to tie together nance and the entire economy in one elegant theory. For example, RobertMerton published “An Intertemporal Capital Asset Pricing Model” in 1973, whichshowed how to generalize the capital asset pricing model to a comprehensiveintertemporal general equilibrium model. Robert Lucas published “Asset Prices inan Exchange Economy” in 1978, which showed that in a rational expectationsgeneral equilibrium, rational asset prices may have a forecastable element that isrelated to the forecastability of consumption. Douglas Breeden published histheory of “consumption betas” in 1979, where a stock’s beta (which measures thesensitivity of its return compared to some index) was determined by the correlationyRobert J. Shiller is the Stanley B. Resor Professor of Economics and also afliated with theCowles Foundation and the International Center for Finance, Yale University, New Haven,Connecticut. He is a Research A ssociate at the National Bureau of Economic Research,Cambridge, Massachusetts. His e-mail address is [email protected] .Journal of Economic Perspectives—Volume 17, Number 1—Winter 2003—Pages 83–104of the stock’s return with per capita consumption. These were exciting theoreticaladvances at the time. In 1973, the  rst edition of Burton Malkiel’s acclaimed book,A Random Walk Down Wall Street, appeared, which conveyed this excitement to awider audience.In the decade of the 1970s, I was a graduate student writing a Ph.D. dissertationon rational expectations models and an assistant and associate professor, and I wasmostly caught up in the excitement of the time. One could easily wish that thesemodels were true descriptions of the world around us, for it would then be awonderful advance for our profession. We would have powerful tools to study andto quantify the  nancial world around us.Wishful thinking can dominate much of the work of a profession for a decade,but not inde nitely. The 1970s already saw the beginnings of some disquiet overthese models and a tendency to push them somewhat aside in favor of a moreeclectic way of thinking about  nancial markets and the economy. Browsing todayagain through  nance journals from the 1970s, one sees some beginnings ofreports of anomalies that didn’t seem likely to square with the ef cient marketstheory, even if they were not presented as signi cant evidence against the theory.For example, Eugene Fama’s 1970 article, “Ef cient Capital Markets: A Review ofEmpirical Work,” while highly enthusiastic in its conclusions for market ef ciency,did report some anomalies like slight serial dependencies in stock market returns,though with the tone of pointing out how small the anomalies were.The 1980s and Excess VolatilityFrom my perspective, the 1980s were a time of important academic discussionof the consistency of the ef cient markets model for the aggregate stock marketwith econometric evidence about the time series properties of prices, dividends andearnings. Of particular concern was whether these stocks show excess volatilityrelative to what would be predicted by the ef cient markets model.The anomalies that had been discovered might be considered at worst smalldepartures from the fundamental truth of market ef ciency, but if most of thevolatility in the stock market was unexplained, it would call into question the basicunderpinnings of the entire ef cient markets theory. The anomaly represented bythe notion of excess volatility seems to be much more troubling for ef ciencymarkets theory than some other  nancial anomalies, such as the January effect orthe day-of-the-week effect.1The volatility anomaly is much deeper than thoserepresented by price stickiness or tatonnement or even by exchange-rate overshoot-ing. The evidence regarding excess volatility seems, to some observers at least, toimply that changes in prices occur for no fundamental reason at all, that they occurbecause of such things as “sunspots” or “animal spirits” or just mass psychology.The ef cient markets model can be stated as asserting that the price Ptof a1A good discussion of the major anomalies, and the evidence for them, is in Siegel (2002).84 Journal of Economic Perspectivesshare (or of a portfolio of shares representing an index) equals the mathematicalexpectation, conditional on all information available at the time, of the presentvalue P*tof actual subsequent dividends accruing to that share (or portfolio ofshares). P*tis not known at time t and has to be forecasted. Ef cient markets say thatprice equals the optimal forecast of it.Different forms of the ef cient markets model differ in the choice of thediscount rate in the present value, but the general ef cient markets model can bewritten just as Pt5 EtP*t, where Etrefers to mathematical expectation conditionalon public information available at time t. This equation asserts that any surprisingmovements in the stock market must have at their origin some new informationabout the fundamental value P*t.It follows from the ef cient markets model that P*t5 Pt1 Ut, where Utis aforecast error. The forecast error Utmust be uncorrelated with any informationvariable available at time t, otherwise the forecast would not be optimal; it wouldnot be taking into account all information. Since the price Ptitself is informationat time t, Ptand Utmust