We examine aggregate idiosyncratic volatility in 23 developed equity markets, measured using various methodologies. We find no evidence of upward trends after extending the sample to 2008. Instead, idiosyncratic volatility is well described by a stationary autoregressive process that occasionally switches into a higher-variance regime that has relatively short duration. We also document that idiosyncratic volatility is highly correlated across countries. Most of the time variation in idiosyncratic volatility can be attributed to variation in a growth opportunity proxy, total (U.S.) market volatility, and in most specifications, the variance premium, a business cycle sensitive risk indicator.

We present a theory of the linkages between corporate governance, corporate finance, and the real sector of an economy. Using a structural model of industry equilibrium with endogenous entry, we show that poor corporate governance leads to low levels of competition, and to firms with high insider ownership and leverage. In contrast, good corporate governance promotes the adoption of more efficient technologies and development of sectors more exposed to moral hazard. We use our model to study equity market liberalization, and we show that liberalizations facilitate entry and adoption of more productive technologies, especially in countries with good corporate governance.

I analyze optimal loan modification schemes in a stochastic home price and stochastic interest-rate environment. Lenders maximize loan values by managing the borrower’s option to default on the loan and prepayment option. Given negative equity, controlling for the borrower’s ability to pay, rate reductions and maturity extensions result in a higher probability of redefault by homeowners even after modification of their loans. In contrast, loan write-downs (the Principal Principle), not a favored recipe, are value maximizing for the lender. A shared-appreciation mortgage enhances the ability to pay, mitigates adverse selection, and reduces the present value of expected deadweight foreclosure costs.

We investigate how differences in regulation regarding banking-commerce integration and banking sector concentration influence loan spreads across 29 countries. Theoretical research posits conflicting effects based on agency costs, information asymmetry costs, and market power. Increased integration is associated with lower loan spreads in countries with low concentration, but moving to high levels of integration increases spreads in countries with high concentration. Starting from lower levels, an increase in integration is associated with an increase in informational efficiency that disappears at higher levels of integration. We also show that market concentration affects loan spreads differently under high-, medium-, and low-integration regimes.

We test whether asymmetric preferences for losses versus gains affect the prices of cash flow versus discount rate risk. We construct a return decomposition distinguishing cash flow and discount rate betas in up and down markets. Using U.S. data, we find that downside cash flow and discount rate betas carry the largest premia. Downside cash flow risk is priced consistently across different samples, periods, and return decomposition methods. It is the only component of beta with significant out-of-sample predictive ability. Downside cash flow premia mainly occur for small stocks, while large stocks are compensated for symmetric cash-flow-related risk.

We study after-hours trading (AHT), price contributions, and price discovery following quarterly earnings announcements released outside of the normal trading hours. For Standard & Poor’s (S&P) 500 index stocks from 2004–2008, AHT is heightened on announcement days. A significant portion of the price change and price discovery occurs immediately after the earnings releases. Prices in AHT show a large degree of informational efficiency, further demonstrating the importance of price discovery in AHT. We also provide evidence suggesting that firms prefer after-hours earnings announcements, as trades are mainly from informed traders, and those trades are relied upon to convey information to the general public.

Model selection (i.e., the choice of an asset pricing model to the exclusion of competing models) is an inherently misguided strategy when the true model is unavailable to the researcher. This paper illustrates the advantages of a model pooling approach in characterizing the cross section of stock returns. The optimal pool combines models using the log predictive score criterion, a measure of the out-of-sample performance of each model, and consistently outperforms the best individual model. The benefits to model pooling are most pronounced during periods of economic stress, and it is a valuable tool for asset allocation decisions.

When managing risk, frequently only imperfect hedging instruments are at hand. We show how to optimally cross-hedge risk when the spread between the hedging instrument and the risk is stationary. For linear risk positions we derive explicit formulas for the hedge error, and for nonlinear positions we show how to obtain numerically efficient estimates. Finally, we demonstrate that even in cases with no clear-cut decision concerning the stationarity of the spread, it is better to allow for mean reversion of the spread rather than to neglect it.