In this paper, I develop a model in which risk-averse investors possess private information regarding both a stock’s expected payoff and its risk. These investors trade in the stock and a derivative whose payoff is driven by the stock’s risk. In equilibrium, the derivative is used to speculate on the stock’s risk and to hedge against adverse fluctuations in the stock’s risk. I analyze the derivative price and variance risk premium that arise in this equilibrium and their predictive power for stock returns. Finally, I examine the relationship between prices and trading volume in the stock and derivative. Received July 31, 2017; editorial decision December 3, 2018 by Editor Stijn Van Nieuwerburgh. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

[In this paper, I develop a model in which risk-averse investors possess private information regarding both a stock’s expected payoff and its risk. These investors trade in the stock and a derivative whose payoff is driven by the stock’s risk. In equilibrium, the derivative is used to speculate on the stock’s risk and to hedge against adverse fluctuations in the stock’s risk. I analyze the derivative price and variance risk premium that arise in this equilibrium and their predictive power for stock returns. Finally, I examine the relationship between prices and trading volume in the stock and derivative.]

This paper studies how public information regarding a firm’s riskiness affects investors’ incentives to acquire information about the firm and the firm’s ability to learn decision-useful information from its price. I find that risk information complements investor learning by informing investors of when it is most lucrative to investigate the firm, thereby reducing liquidity. Furthermore, risk information causes the firm’s price to contain more information when the firm’s investment decisions have the greatest impact on its value, thereby improving real efficiency. Extensions of the model suggest that the impact of risk information on real efficiency may deteriorate when the firm’s manager is excessively exposed to idiosyncratic risk, when the firm’s shareholders are excessively averse to such risk, or when the disclosure concerns a “downside risk.” In sum, my analysis suggests that information regarding firms’ expected values and information regarding firms’ risks significantly differ in their effects on the capital market.

ABSTRACT We develop a measure of how information events impact investors' expectations of risk. The measure is broadly applicable and simple to implement. We derive it from an option‐pricing model, where investors anticipate an announcement that simultaneously conveys information on the announcer's expected future cash flows and risk profile. We empirically implement the measure using firms' earnings announcements, showing that it closely aligns with our model's predictions and offers strong forecasting power for firms' risk profiles, costs of capital, and future investments. We further highlight pitfalls of using simple changes in option‐implied volatilities to study information gleaned from earnings announcements. Finally, we apply our measure to study disclosure regulation, the efficacy of text‐based proxies, and market‐wide events, which we use to illustrate our measure's uses, and illuminate its potential limitations.

Extensive evidence suggests that managers strategically choose the complexity of their descriptive disclosures. However, their motives in doing so appear mixed, as complex disclosures are used to obfuscate in some cases and to provide information in others. Building on these observations, we first identify a novel stylized fact: disclosure complexity is non-monotonic in firm performance. We develop a model of disclosure complexity that incorporates the dual roles of complexity and can explain this stylized fact. In the model, a manager discloses to investors of heterogeneous sophistication and can adjust the complexity of the disclosure to either provide more precise information or to obfuscate. When the firm's investor base is largely unsophisticated, the manager issues a complex disclosure only upon observing negative news. In contrast, when the firm's investor base is more sophisticated, the manager issues a complex disclosure upon observing either highly positive or negative news. As a result, the market may react more positively to complex information releases than to simple releases, complex disclosures generate heightened return volatility, and firms with more inherently complex information are more likely to use their discretion to simplify their disclosures.

ABSTRACT The impact of earnings announcements (EAs) on investor uncertainty depends not only on how much new information they contain but also on how long it would take comparable information to arrive in the future through alternative sources, which I term “earnings horizon.” Using a structural model of periodic EAs, I show that earnings horizon is not captured by standard empirical measures of earnings informativeness or timeliness based on the event-study approach. However, earnings horizon can be estimated using patterns in return volatility over firms’ reporting cycles, which indicate that EAs have a short horizon and thus reduce investor uncertainty by one-third the amount suggested by event studies. Moreover, these patterns indicate that it takes investors considerably longer than the three- to five-day windows commonly applied in event studies to fully process EAs and that more frequent financial reporting may significantly enhance EAs’ informativeness. Data Availability: Data are available from the public sources cited in the text. JEL Classifications: C58; D82; D84; G10; G12; G14; G30.

ABSTRACT In this paper, I develop a measure of the difference in the amount of information that investors expect a forthcoming disclosure to contain should it reveal good news versus bad news (the disclosure’s “asymmetry”). To do so, I first show that this asymmetry is linked to the skewness of returns that the disclosure creates. I then show that this skewness can be measured using a weighted change in option-implied return skewness leading up to the disclosure’s release. The measure’s ability to capture investors’ prior beliefs regarding asymmetry is advantageous when studying ex ante decisions including contracting and information acquisition choices. I implement it on a sample of large firms’ quarterly earnings announcements, finding evidence that investors anticipate cross-sectional but not time-series variation in earnings’ asymmetry.

When valuing a firm, investors must assess not only its expected future cash flows but also the systematic risk inherent in these cash flows. In this paper, we model the process by which investors may learn about firms' betas from earnings and how this learning process affects the relationship between earnings, announcement returns, and expected future returns. The model's main predictions are: (i) earnings response coefficients vary with macroeconomic conditions and are lower in upswings than downturns; (ii) earnings positively and negatively predict future returns in economic upswings and downturns, respectively, leading to return autocorrelation; and (iii) real earnings management rises in economic downturns and contributes to systematic risk in the economy. These predictions are directly attributable to investors' uncertainty regarding firms' exposures to systematic risk.

We study debt and equity valuation when investors have private information and may exhibit differences of opinion. Our model generates several predictions that are consistent with empirical evidence but difficult to reconcile with traditional models. Belief dispersion relates to expected equity and debt returns in opposite directions. Similarly, expected debt (equity) returns typically increase (decrease) with default risk, though these relationships reverse for firms close to bankruptcy. Firms’ capital structures affect their valuations even without classical capital structure frictions (e.g., tax shields, distress costs) – when liquidity is higher in the equity than in the debt market, leverage can raise firm value.