Investor Attention Correction in Asset Pricing Models: An Empirical Study Based on Internet Search Index and the A-Share Market

Abstract

In the context of digitalization and information explosion, traditional Capital Asset Pricing Models (CAPM) based on the assumptions of efficient markets and rational actors are insufficient to fully explain many anomalies in returns in the China’s A-share market, which is dominated by retail investors and experiences significant fluctuations in investor sentiment. This study uses individual stock data from 2015 to 2024 and, based on the Fama-French three-factor model, introduces an “abnormal investor attention” index constructed based on individual stock online search indices to build an extended pricing model, systematically examining its impact on stock excess returns. The study finds that abnormal attention has a significant positive impact on current excess returns, supporting the “attention-driven buying” hypothesis. Secondly, this effect exhibits scale heterogeneity, with a stronger driving effect on the stock prices of large-cap companies than small-cap companies. Finally, the previous abnormal concern has a great negative “reversal” effect on the current income. This shows that the market has its own function to correct the price deviation caused by excessive attention. This study reveals the complete working process of “eye-catching price correction” This can not only give us a new view of market mentality and price efficiency, but also help investors to find trading signals and pay attention to reversal risks, and also help regulatory authorities to monitor abnormal fluctuations and guide reasonable investment.