While recent theoretical and empirical work suggests that the physical skewness of a stock’s future discrete return distribution prices stocks, it does not tell us over which return horizon(s) that physical skewness is priced. Developing a novel block bootstrap estimator that allows us to calculate realized return skewness over arbitrary horizons, we aim to identify those return horizons. In doing so, we first show that our block bootstrap estimator produces more accurate realized skewness estimates than other recent estimators do. Next, we report that the existing skewness proxies used in the empirical asset pricing literature differ in how well they predict skewness over short or long return horizons. Finally, we reveal that the skewness pricing evidence documented in the empirical asset pricing literature is mostly driven by skewness over short (and not long) return horizons.

We show that the negative relation between real investments and future stock returns is primarily driven by the subsample of firms building additional capacity. We develop a real options model to rationalize that evidence based on the premise that firms need to learn how to best operate modern capacity vintages, inducing idiosyncratic uncertainty in that capacity’s production costs over the learning period. Conversely, the uncertainty lowers the expected return of firms with newly built capacity until it is resolved. Further evidence based on profit sensitivities to aggregate conditions; analyst forecast-error volatilities; and high- versus low-tech industry subsamples supports our uncertainty explanation.

The study of Ferguson and Shockley (2003) shows that, if the Merton (1974) model can reflect reality, the omission of debt claims from the market portfolio proxy may explain the poor pricing ability of the CAPM in empirical tests. We critically re-assess this argument by first reviewing existing, but also new avenues through which the Merton (1974) model can point to a systematic bias in market beta estimates. However, we also show that some avenues are diversifiable, and that they all rely on excessive economy-wide default risk to create a non-negligible bias. We then use the Merton (1974) model to proxy for the total debt portfolio, but find that its application in empirical tests cannot improve pricing performance. We conclude that there are (so far) no valid theoretical reasons to believe that omitted debt claims undermine CAPM tests.

We study whether industrial firms risk-shift in response to distress risk increases induced through hurricane strikes. Using new proxies capturing deliberate managerial decisions about the risk of a firm’s operating segment portfolio, differences tests suggest that hurricane strikes prompt moderately, but not highly, distressed firms to skew their asset mixes toward riskier segments by shutting down low-risk, high-average-Q segments. In turn, the moderately distressed firms observe abnormally high failure rates after a hurricane strike. Employing covenant violation data, we offer further evidence that creditor control prevents highly distressed firms from raising their risk. Our conclusions extend those of other studies by suggesting that moderate distress risk levels can lead the managers of industrial firms to not only engage in risk-taking, but, in fact, in risk-shifting.

We use a stochastic frontier model to obtain a stock‐level estimate of the difference between a firm's installed production capacity and its optimal capacity. We show that this “capacity overhang” estimate relates significantly negatively to the cross section of stock returns, even when controlling for popular pricing factors. The negative relation persists among small and large stocks, stocks with more or less reversible investments, and in good and bad economic states. Capacity overhang helps explain momentum and profitability anomalies, but not value and investment anomalies. Our evidence supports real options models of the firm featuring valuable divestment options.

We study the effect of an asset’s volatility on the expected returns of European options on the asset. Deriving predictions from a stochastic discount factor model, we show that the effect depends on whether variations in the asset’s volatility are driven by systematic or idiosyncratic volatility. While idiosyncratic-volatility-induced variations only affect the option elasticity, systematic-volatility-induced variations also oppositely affect the expected return of the asset. Since the expected asset return (elasticity) effect dominates for options with more linear (non-linear) payoffs, systematic volatility prices sufficiently in-the-money (out-of-the-money) options with the opposite (same) sign as idiosyncratic volatility. Using single-stock calls as test assets, double-sorted portfolios and Fama–MacBeth (1973) regressions broadly support the model’s predictions.

In this article, we show that only distressed firms not identified as distressed by creditors are able to transfer wealth from creditors to shareholders. Using the number of years to future bankruptcy as a proxy for genuine distress and measures based on observable firm characteristics as proxies for perceived distress, genuinely distressed firms incorrectly perceived as healthy cut payouts to shareholders more slowly and invest more aggressively as uncertainty increases than correctly identified distressed firms. Consistent with the idea that incorrectly identified distressed firms actively hide their troubles, we show that they tend to follow more aggressive accounting policies and often resort to earnings misstatements. We also show that they are often not restricted by covenants and can borrow further debt capital at affordable rates, suggesting that a lack of monitoring by creditors allows them to transfer wealth to shareholders.

We argue that firms’ ability to disinvest real assets helps rationalize the negative distress premiums in stocks, bonds, and, as we show, loans and firm assets. Using a real options model in which shareholders and debtholders share disinvestment proceeds, the model suggests that the stock (debt) distress premium becomes more negative with the proceeds paid out to that class, and that both premiums can be negative when debtholders receive most of the proceeds. Using hard-asset disinvestment-ability proxies, the stock (bond or loan) distress premium becomes less (more) negative with those proxies, possibly suggesting that shareholders benefit more strongly from nonsecured-asset disinvestments.

We show that book-to-market, size, and momentum capture cross-sectional variation in exposures to a broad set of macroeconomic factors identified in the prior literature as potentially important for pricing equities. The factors considered include innovations in economic growth expectations, inflation, the aggregate survival probability, the term structure of interest rates, and the exchange rate. Factor mimicking portfolios constructed on the basis of book-to-market, size, and momentum therefore, serve as proxy composite macroeconomic risk factors. Conditional and unconditional cross-sectional asset pricing tests indicate that most of the macroeconomic factors considered are priced. The performance of an asset pricing model based on the macroeconomic factors is comparable to the performance of the Fama and French (1993) model. However, the momentum factor is found to contain incremental information for asset pricing.

France's Ordonnance 2006‐346 repudiated the notion of possessory ownership in the Napoleonic Code, easing the pledge of physical assets in a country where credit was highly concentrated. A differences‐test strategy shows that firms operating newly pledgeable assets significantly increased their borrowing following the reform. Small, young, and financially constrained businesses benefitted the most, observing improved credit access and real‐side outcomes. Start‐ups emerged with higher “at‐inception” leverage, located farther from large cities, with more assets‐in‐place than before. Their exit and bankruptcy rates declined. Spatial analyses show that the reform reached firms in rural areas, reducing credit access inequality across France's countryside.