This study presents a model in which behavioral investors shape their current expectations based on statistical analysis of historical non-disclosure events. Investors may hold overly optimistic expectations following a non-disclosure event, thereby disrupting unraveling toward forthcoming disclosures. While a regulator can mandate disclosure, this protective intervention has its drawbacks. Overprotection prevents investors from learning from losses and leads to cycles of high compliance followed by high mispricing when innovations in transactions render current regulations ineffective. An unregulated market, on the other hand, tends toward high transparency over time. The model further explains negative market reactions to regulation, an association between price drift and transparency, reversals in market confidence, and that regulators should favor laissez-faire in times of investor pessimism. Further implications are explored for regulations that facilitate learning and prevent cycles.