I assess time-series return predictability using a weighted least squares estimator that is around 25% more efficient than ordinary least squares (OLS) because it incorporates timevarying volatility into its point estimates. Traditional predictors, such as the dividend yield, perform better in-and out-of-sample when using my estimator, indicating the insignificant OLS estimates may be false negatives driven by a lack of power. Some newer predictors, such as the variance risk premium and the president's political party, are insignificant when using my estimator, indicating the significant OLS estimates may be false positives driven by a few periods with high expected volatility. (JEL G10, G11, G12)

The shape of the Chicago Board Options Exchange Volatility Index (VIX) term structure conveys information about the price of variance risk rather than expected changes in the VIX, a rejection of the expectations hypothesis. The second principal component, SLOPE, summarizes nearly all this information, predicting the excess returns of synthetic Standard & Poor’s (S&P) 500 variance swaps, VIX futures, and S&P 500 straddles for all maturities and to the exclusion of the rest of the term structure. SLOPE’s predictability is incremental to other proxies for the conditional variance risk premia, economically significant, and inconsistent with standard asset pricing models.

ABSTRACT We show that the cost of trading on negative news, relative to positive news, increases before earnings announcements. Our evidence suggests that this asymmetry is due to financial intermediaries reducing their exposure to announcement risks by providing liquidity asymmetrically. This asymmetry creates a predictable upward bias in prices that increases preannouncement, and subsequently reverses, confounding short‐window announcement returns as measures of earnings news and risk premia. These findings provide an alternative explanation for asymmetric return reactions to firms' earnings news, and help explain puzzling prior evidence that announcement risk premia precede the actual announcements. Our study informs methods for research centering on earnings announcements and offers a possible explanation for patterns in returns around anticipated periods of heightened inventory risks, including alternative firm‐level, industry‐level, and macroeconomic information events.

We examine the information content of option and equity volumes when trade direction is unobserved. In a multimarket asymmetric information model, equity short-sale costs result in a negative relation between relative option volume and future firm value. In our empirical tests, firms in the lowest decile of the option to stock volume ratio (O/S) outperform the highest decile by 0.34% per week (19.3% annualized). Our model and empirics both indicate that O/S is a stronger signal when short-sale costs are high or option leverage is low. O/S also predicts future firm-specific earnings news, consistent with O/S reflecting private information.

Using novel earnings calendar data, we show that firms’ advanced scheduling of earnings announcement dates foreshadows their earnings news. Firms that schedule later-than-expected announcement dates subsequently announce worse news than those scheduling earlier-than-expected announcement dates. Despite scheduling disclosures being observable weeks ahead of earnings announcements, we show that equity markets fail to reflect the information in these disclosures until the announcement itself. By also showing that option markets respond efficiently to volatility-timing information embedded in the same scheduling disclosures, we provide novel evidence that markets fail to react to information about future earnings despite investors immediately trading on the underlying signal.

We measure the impact of reputation for proxy fighting on investor activism by estimating a dynamic model in which activists engage a sequence of target firms. Our estimation produces an evolving reputation measure for each activist and quantifies its impact on campaign frequency and outcomes. We find that high reputation activists initiate 3.5 times as many campaigns and extract 85% more settlements from targets, and that reputation-building incentives explain 20% of campaign initiations and 19% of proxy fights. Our estimates indicate these reputation effects combine to nearly double the value that activism adds for target shareholders.

We study the effects of time-varying volatility and investment horizon on the economic significance of stock market return predictability from the perspective of Bayesian investors. Using a vector autoregression framework with stochastic volatility (SV) in market returns and predictor variables, we assess a broad set of twenty-six predictors with both in-sample and out-of-sample designs. Volatility and horizon are critically important for assessing return predictors, as these factors affect how an investor learns about predictability and how she chooses to invest based on return forecasts. We find that statistically strong predictors can be economically unimportant if they tend to take extreme values in high volatility periods, have low persistence, or follow distributions with fat tails. Several popular predictors exhibit these properties such that their impressive statistical results do not translate into large economic gains. We also demonstrate that incorporating SV leads to substantial utility gains in real-time forecasting.

We establish a link between firms managing investors’ performance expectations, earnings announcement premiums, and cyclical patterns (i.e., seasonalities) in returns. Firms that are more likely to manage expectations toward beatable levels predictably earn lower returns before, and higher returns during, their earnings announcements. This pattern repeats across firms’ fiscal quarters, suggesting firms manufacture positive “surprises” by negatively biasing investors’ expectations ahead of announcing earnings. We corroborate these findings using non-price-based outcomes indicative of expectations management. Together, our findings are consistent with the pressure for firms to meet earnings targets shaping the cross-section of firms’ stock returns.