Secular Mean Reversion and Long-Run Predictability of the Stock Market

Abstract

Empirical financial literature documents the evidence of mean reversion in stock prices and the absence of out-of-sample return predictability over periods shorter than 10 years. The goal of this paper is to test the random walk hypothesis in stock prices and return predictability over periods longer than 10 years. Specifically, using 141 years of data, this paper begins by performing formal tests of the random walk hypothesis in the prices of the real S&P Composite Index over increasing time horizons up to 40 years. Even though our results cannot support the conventional wisdom which says that the stock market is safer for long-term investors, our findings speak in favor of the mean reversion hypothesis. In particular, we find statistically significant in-sample evidence that past 15-17 year returns are able to predict future 15-17 year returns. This finding is robust to the choice of data source, deflator, and test statistic. The paper continues by investigating the out-of-sample performance of long-horizon return forecast based on the mean-reverting model. These latter tests demonstrate that the forecast accuracy provided by the mean-reverting model is statistically significantly better than the forecast accuracy provided by the naive historical-mean model. Moreover, we show that the predictive ability of the mean-reverting model is economically significant and translates into substantial performance gains.