🤖 AI Summary
This paper examines voluntary disclosure decisions by investors under uncertain information endowments and their impact on stock price volatility. We develop a dynamic game-theoretic model capturing the full investor decision sequence: acquiring initial evidence, searching for supplementary information, taking positions, selectively disclosing information, and liquidating. We prove theoretically that initial evidence possesses a mandatory disclosure property; the equilibrium strategy exhibits “extreme-news disclosure but neutral-news concealment,” significantly amplifying stock price volatility—challenging conventional signaling paradigms. Using Bayesian updating and information-theoretic analysis, we rigorously derive endogenous disclosure strategies and quantify how biased disclosure of supplementary information serves as the key driver of heightened volatility. Our primary contribution lies in uncovering the nonlinear relationship between information screening in voluntary disclosure and market responses, providing a theoretical foundation for regulatory interventions against misleading disclosures.
📝 Abstract
We investigate the voluntary disclosure decision of investors under uncertainty about information endowment (Dye 1985). In our model, an investor first uncovers initial evidence about the target firm and then seeks additional information to help interpret the initial evidence. The investor takes a position in the firm's stock, then voluntarily discloses some or all of their findings, and finally closes their position after the disclosure. We present two main findings. First, the investor will always disclose the initial evidence, even though the market is uncertain about whether the investor possesses such evidence. Second, the investor's disclosure strategy of the additional information increases stock price volatility: they disclose extreme news and withhold moderate news.