Search

We document that regulatory enforcement actions for financial misrepresentation cluster in industry-specific waves and that wave-related enforcement has information spillovers on industry peer firms. Waves and spillovers have significant effects on share prices. Early-wave target firms have the largest short-run losses in share values and the largest information spillovers on industry peer firms. Late-wave targets’ short-run losses are smaller, but not because they involve less costly instances of misconduct. Rather, late-wave targets are subject to more information spillovers from earlier in the wave. These results indicate that prices incorporate changes in the likelihood that a firm will face wave-related enforcement action for financial misconduct. Short-window share-price losses understate the total share-price impact, particularly for firms whose financial misrepresentation is revealed late in an enforcement wave. This paper was accepted by David Simchi-Levi, finance. Supplemental Material: The internet appendix and data are available at https://doi.org/10.1287/mnsc.2023.4711 .

Exploiting a regulatory change in short‐sale constraints (Regulation SHO) as a natural experiment, this paper examines the effect of short‐sale constraints on informational efficiency of stock prices to private information. I find that short‐sellers act as informed traders prior to forthcoming analyst news and trade on negative private information. When short‐sale constraints are relaxed for pilot stocks (treatment group), both trading volume and stock price sensitivity increase prior to the analyst announcement for bad news but not for good news, relative to that of nonpilot stocks (control group). The findings are consistent with the Diamond and Verrecchia model that predicts that short‐selling increases the speed of adjustment of stock prices to private negative information. In the cross‐section, the effect of Reg SHO is stronger in stocks of firms with weak and uncertain information environments (i.e., small firms and firms with high analyst forecast dispersion).

This study examines the changes in trading volume around quarterly earnings announcements in regard to market uncertainty. When market conditions are volatile, investors face difficulty in predicting future cash flows and their beliefs are more dispersed. Under this larger dispersion in prior beliefs, investors learn more from earnings news, but they are also likely to differ in their interpretations. This leads to increased trading volume around earnings announcements under high market uncertainty. I find that abnormal trading volume around the 2-day announcement window increase with market return volatility and the VIX index. The increase in trading volume is more pronounced for firms with more market-wide information and larger firms, which tend to have larger market earnings components.

Consistent with Bayesian learning models, I find that two types of uncertainty—market uncertainty and firm-signal uncertainty—have opposite effects on investors’ learning from new information. I provide novel evidence that investor learning increases with the level of prior market uncertainty and decreases with firm-signal uncertainty (i.e., signal precision). Specifically, I find that the stock price response to earnings announcements increases with market volatility and decreases with earnings volatility. The results indicate that investor learning increases linearly with market uncertainty and decreases nonlinearly with firm-signal uncertainty. The effect of market uncertainty is stronger for large firms, firms with more market information in their returns, and firms with more institutional ownership.

This paper examines the causal effect of short selling on analyst forecast precision by exploiting a regulatory change in short-sale constraints (Regulation SHO) as a natural experiment. I find that short selling increases analysts’ rounding of forecasts, which indicates that analysts allocate less effort to gathering precise information on firms with downward price pressure. In the cross-section, the effect of short selling on analyst forecast precision is stronger for firms with more firm-specific information and firms with low levels of institutional holdings.

We examine how analysts’ changing incentives driven by changes in market uncertainty affect their forecast optimism. Analysts issue more optimistically biased earnings forecasts and buy recommendations under high market uncertainty (VIX). The lower reputational costs and larger benefits of optimistic output explain the increased optimistic output: Analysts are less likely to be penalized for inaccuracy and can stimulate more trading activity from optimistically biased output when market uncertainty is high. We find that the likelihood of analysts’ turnover decreases, while the trading volume associated with optimistic output increases, with VIX. No evidence suggests that analysts’ self-selection affects our findings on optimism and market uncertainty.

This paper shows that variation in economy-wide uncertainty causes asymmetric stock price responses to firm earnings surprises. The uncertainty that attends bad earnings news that arrives during expansions with greater economy-wide uncertainty occasions larger price declines. This is because news inconsistent with investors� prior beliefs about the state of the economy increases uncertainty, which amplifies the negative cash flow effects contained in bad earnings news. Asymmetrically, the positive cash flow effect of good earnings news that arrives during recessions is offset by increased investor uncertainty, which results in relatively smaller price reactions to the good news. This is consistent with Veronesi's rational expectations equilibrium model, which shows that investors demand higher expected returns in the face of greater uncertainty.

Consistent with the predictions from a stylized Bayesian learning model, this study shows the opposite effects of two types of uncertainty— market uncertainty and firm-specific uncertainty — on investors’ learning from new information. I provide novel evidence that investor learning increases with the level of market uncertainty, and decreases with firm-specific signal uncertainty. The stock price responses to earnings announcements increase when market volatility is high, whereas the price responses decrease when a firm’s cash flow volatility is high. I do not find evidence of alternative explanations such as liquidity effects, increased firm risk, or differences in the information environment under market uncertainty.

This paper studies how changes in analysts’ incentives driven by changes in market uncertainty affect analyst output, under a simple utility-maximizing framework. We find that analysts issue more optimistically biased forecasts and more buy recommendations under high market uncertainty (VIX). The increase in optimistic output can be explained by lower reputational costs and larger benefits of optimistic output. We posit that analysts are less likely to be penalized for inaccuracy, while they can stimulate more trading activity from optimistically biased output, when market uncertainty is high. Accordingly, we find that the likelihood of analysts’ turnover decreases, while the trading volume associated with optimistic output increases, with the level ojavascript:void(0);f VIX.

This paper examines security analysts’ tendency to rely on category-level (e.g. industry) information as opposed to firm-specific information in issuing earnings forecasts. We find that analysts who rely more on category-level information have larger forecast errors, issue less frequent forecasts, have less impact on stock prices, and are more likely to experience job turnover. Our results are consistent with analysts being subject to limited attention, where psychological evidence predicts that attention-constrained market participants oversimplify information processing by relying on coarse category-level information. Further, analysts’ limited attention has a significant association with their forecasting ability, stock price impact, and career outcomes.

I show that variation in economy-wide uncertainty causes asymmetric stock price responses to firm earnings surprises. The uncertainty that attends bad earnings news that arrives during expansions with greater economy-wide uncertainty occasions larger price declines. This is because news inconsistent with investors’ prior beliefs about the state of the economy increases uncertainty, which amplifies the negative cash flow effects contained in bad earnings news. Asymmetrically, the positive cash flow effect of good earnings news that arrives during recessions is offset by increased investor uncertainty, which results in relatively smaller price reactions to the good news. This consistent with Veronesi’s rational expectations equilibrium model (1999), which shows that investors demand higher expected returns in the face of greater uncertainty.