Chinese Stock Market Return Predictability: Adaptive Complete Subset Regressions

Abstract

AbstractThis paper proposes a new combination framework to explore the Chinese stock market return predictability. While most well‐known predictor variables and simple combinations fail to beat the historical average benchmark, our adaptive complete subset regressions deliver statistically and economically significant out‐of‐sample performance. The subset, in which each regression includes five predictors, produces a significant statistic of 8.00% for January 2006 to September 2014. A mean‐variance investor who uses the adaptive subset regressions forecasts, instead of the historical average forecasts, can obtain sizable utility gains of 7.60% per annum. The results of our paper suggest that there is significant predictability in the Chinese aggregate stock market portfolio.