Investor attention and anomalies: Evidence from the Chinese stock market

Abstract

This paper investigates how investor attention influences anomalies in the Chinese stock market. Utilizing data from 2011 to 2022, we propose investor attention composite indices using the partial least squares method, combining information from 11 attention proxies. By analyzing the newly proposed index, we explore the impact of investor attention on stock market anomalies. Our results demonstrate that investor attention has a positive effect on concurrent market anomalies, a relationship that remains robust even when considering factors such as the Fama-French three factors and investor sentiment. Further examination utilizing a composite index of investor attention derived from scaled principal component analysis yields similar results. Notably, our research indicates that investor attention significantly impacts anomaly returns in the subsequent month, suggesting potential forecasting capabilities.