Secular Mean Reversion and Long‐Run Predictability of the Stock Market
28 Pages Posted: 10 Oct 2017
Date Written: October 2017
The empirical financial literature reports evidence of mean reversion in stock prices and the absence of out‐of‐sample return predictability over horizons shorter than 10 years. Anecdotal evidence suggests the presence of mean reversion in stock prices and return predictability over horizons longer than 10 years, but thus far, there is no empirical evidence confirming such anecdotal evidence. The goal of this paper is to fill this gap in the literature. 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 of up to 40 years. Although our results cannot support the conventional wisdom 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 the 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 forecasting 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.
Keywords: boostrap simulation, long run, mean reversion, random walk, predictability, stock returns
JEL Classification: C12, C14, C22, G12, G14, G17
Suggested Citation: Suggested Citation