Over the last twenty years, the field of behavioral finance has grown from a startup operation into a mature enterprise, with well-developed bodies of both theory and empirical evidence. On the empirical side, the benchmark null hypothesis is that one should not be able to forecast a stock’s return with anything other than measures of its riskiness, such as its beta; this hypothesis embodies the familiar idea that any other form of predictability would represent a profitable trading rule and hence a free lunch to investors. Yet in a striking rejection of this null, a large catalog of variables with no apparent connection to risk have been shown to forecast stock returns, both in the time series and the cross-section. Many of these results have been replicated in a variety of samples and have stood up sufficiently well that they are generally considered to be established facts.