Beschreibung:
We empirically investigate the relation between anomaly portfolio returns and market return predictability in the Chinese stock market. Using 132 long-leg, short-leg, and long-short anomaly portfolio returns, we employ several shrinkage-based statistical learning methods to capture predictive signals of the anomalies in a high-dimensional setting. We find statistically and economically significant return predictability using long- and short-leg anomaly portfolio returns. Moreover, high arbitrage risk enhances forecasting performance, supporting that the predictability stems from mispricing correction persistence. Unlike the U.S. stock market, we find little evidence that the long-short anomaly portfolios can help predict market return due to the low persistence of asymmetric mispricing correction. We provide simulation evidence to sharpen our understanding of the differences found in the U.S. and Chinese stock markets