Cross-correlations and predictability of stock returns

Abstract

Studies have shown that small stock returns can be partially predicted by the past returns of large stocks (cross-correlations), while a larger body of literature has shown that macroeconomic variables can predict future stock returns. This paper assesses the marginal contribution of cross-correlations after controlling for predictability inherent in lagged macroeconomic variables. Macroeconomic forecasting models generate trading rule profits of up to 0.431% per month, while the inclusion of cross-correlations increases returns to 0.516% per month. Such results suggest that cross-correlations may serve as a proxy for omitted macroeconomic variables in studies of stock market predictability. Macroeconomic variables are more important than cross-correlations in forecasting small stock returns and encompassing tests suggest that the small marginal contribution of cross-correlations is not statistically significant. Copyright © 2001 by John Wiley & Sons, Ltd.