Regressions of multiple-period changes in the log exchange rate on the deviation of the log exchange rate from its "fundamental value," display evidence that long-horizon changes in log nominal exchange rates contain an economically significant predictable component. To account for small-sample bias and size distortion in asymptotic tests, inference is drawn from bootstrap distributions generated under the null hypothesis that the log exchange rate is unpredictable. The bias-adjusted slope coefficients and R^2's increase with the forecast horizon, and the out-of-sample point predictions generally outperform the driftless random walk at the longer horizons.

Regressions of multiple-period changes in the log exchange rate on the deviation of the log exchange rate from its 'fundamental value' display evidence that long-horizon changes in log nominal exchange rates contain an economically significant predictable component. To account for small-sample bias and size distortion in asymptotic tests, inference is drawn from bootstrap distributions generated under the null hypothesis that the log exchange rate is unpredictable. The bias-adjusted slope coefficients and R[superscript]2's increase with the forecast horizon, and the out-of-sample point predictions generally outperform the driftless random walk at the longer horizons.

This paper demonstrates that negative serial correlation in long horizon stock returns is consistent with an equilibrium model of asset pricing. When investors display only a moderate desire to smooth their consumption, commonly used measures of mean reversion in stock prices calculated from historical returns data nearly always lie within a 60 percent confidence interval of the median of the Monte Carlo distributions implied by our equilibrium model. From this evidence, we conclude that the degree of serial correlation in the data could plausibly have been generated by our model.

We study a Lucas asset-pricing model that is standard in all respects, except that the representative agent's subjective beliefs about endowment growth are distorted. Using constant relative risk-aversion (CRRA) utility, with a CRRA coefficient below 10; fluctuating beliefs that exhibit, on average, excessive pessimism over expansions; and excessive optimism over contractions (both ending more quickly than the data suggest), our model is able to match the first and second moments of the equity premium and risk-free rate, as well as the persistence and predictability of excess returns found in the data.