Two essays on the effects of information disclosures on investor behaviors

Abstract

This thesis includes two essays on the impact of information disclosure on investors’ overconfidence and belief updating regarding the future stock price crash risk. The first essay examines how EDGAR implementation affects retail investors’ overconfidence through reducing the acquisition costs of fundamental information costs with online disclosure. The second essay investigates whether implied stock price crash risk is affected within a short window around the management guidance. In the first essay, we investigate whether information acquisition costs impact retail investors’ overconfidence. Overconfidence is one of the most common behavioral biases among market participants in financial markets. Overconfident individuals tend to overestimate the precision of their knowledge and information. Models of financial markets with overconfident traders imply high trading volume, high volatility, and low price informativeness, explaining market anomalies with empirical and experimental evidence. However, these studies assume overconfidence. Using the implementation of the Electronic Data Gathering, Analysis, and Retrieval (EDGAR) system as an exogenous event, we find that overconfidence, measured by retail investors’ trading activities and post-trade performance of stocks, is significantly reduced after firms join the EDGAR platform. The main results hold for both staggered and stacked difference-in-difference analyses. To further support the idea that the reduction in overconfidence is related to the decrease in information acquisition costs and increase in information set, we conduct a subsample analysis by dividing the dataset based on the level of information asymmetry for each firm. The reduction in overconfidence is greater for young firms and growth firms. These findings shed light on the effect of information sets on the overconfidence of retail investors. In the second essay, we investigate whether managers’ voluntary disclosures affect investors’ subjective stock price crash risk. Theoretical models indicate a predictive relationship between a firm’s information environment and stock price crash risk. These models predict that there will be more stock price crashes if firms have less transparent firm-specific bad news. Using option-implied skewness as a measure of investors’ subjective stock price crash risk, we find that investors’ perception of future stock price crash risk decreases immediately after managers disclose bad news and increases after the announcement of good news. Further cross-sectional analysis demonstrates that this decrease in ex-ante stock price crash risk can be attributed to the fact that fewer negative news items are hidden by firms. The increase in ex-ante skewness can potentially be explained if investors suspect that managers strategically hide bad news and disclose good news for their own benefit. To understand the change in investors’ perception of future tail risks, we demonstrate that the change in ex-ante stock price crash risk following earnings guidance disclosure provides additional predictive power for the realized skewness level in the following month. In summary, these two essays shed light on the impact of information disclosure on investors’ trading bias and belief updating regarding to future stock return distribution, providing new empirical evidence.