We argue that arbitrage‐pricing theories (APT) imply the existence of a low‐dimensional nonnegative nonlinear pricing kernel. In contrast to standard constructs of the APT, we do not assume a linear factor structure on the payoffs. This allows us to price both primitive and derivative securities. Semi‐nonparametric techniques are used to estimate the pricing kernel and test the theory. Empirical results using size‐based portfolio returns and yields on bonds reject the nested capital asset‐pricing model and linear APT and support the nonlinear APT. Diagnostics show that the nonlinear model is more capable of explaining variations in small firm returns.

We investigate the time variability of abnormal returns from socially responsible investing (SRI). Using portfolio regressions and event studies on multiple data sources, including analyst ratings, firm announcements, and realized incidents, we find that highly rated SRI stocks outperform lowly rated SRI stocks during good economic times, for example, periods with high market valuations or aggregate consumption, but underperform during bad times, such as recessions. This variation in abnormal returns of high-SR stocks vis-à-vis low SR stocks is consistent with a wealth-dependent investor preference for SR stocks that leads to an increased (decreased) demand for SRI during good (bad) times.

We estimate a regime-switching model for the equity term structure with Bayesian methods. Our approach accounts for the data sample being unrepresentative of the population distribution of regimes. We find that (i) the term structure of expected equity dividend strip returns is downward sloping in recessions and upward sloping in expansions, and (ii) the unconditional term structure of expected equity returns is positively sloped. Our estimation shows that the sample unrepresentativeness induces a downward bias in the estimate of the equity term structure slope. We present a regime-switching consumption-based asset-pricing model that matches the empirical findings.

This paper uses a nonlinear arbitrage‐pricing model, a conditional linear model, and an unconditional linear model to price international equities, bonds, and forward currency contracts. Unlike linear models, the nonlinear arbitrage‐pricing model requires no restrictions on the payoff space, allowing it to price payoffs of options, forward contracts, and other derivative securities. Only the nonlinear arbitrage‐pricing model does an adequate job of explaining the time series behavior of a cross section of international returns.

The paper estimates and examines the empirical plausibility of asset pricing models that attempt to explain features of financial markets such as the size of the equity premium and the volatility of the stock market. In one model, the long-run risks (LRR) model of Bansal and Yaron, low-frequency movements, and time-varying uncertainty in aggregate consumption growth are the key channels for understanding asset prices. In another, as typified by Campbell and Cochrane, habit formation, which generates time-varying risk aversion and consequently time variation in risk premia, is the key channel. These models are fitted to data using simulation estimators. Both models are found to fit the data equally well at conventional significance levels, and they can track quite closely a new measure of realized annual volatility. Further, scrutiny using a rich array of diagnostics suggests that the LRR model is preferred.

How important are volatility fluctuations for asset prices and the macroeconomy? We find that an increase in macroeconomic volatility is associated with an increase in discount rates and a decline in consumption. We develop a framework in which cash flow, discount rate, and volatility risks determine risk premia and show that volatility plays a significant role in explaining the joint dynamics of returns to human capital and equity. Volatility risk carries a sizable positive risk premium and helps account for the cross section of expected returns. Our evidence demonstrates that volatility is important for understanding expected returns and macroeconomic fluctuations.

We show that aggregate consumption risks embodied in cash flows can account for the puzzling differences in risk premia across book‐to‐market, momentum, and size‐sorted portfolios. The dynamics of aggregate consumption and cash flow growth rates, modeled as a vector autoregression, are used to measure the consumption beta of discounted cash flows. Differences in these cash flow betas account for more than 60% of the cross‐sectional variation in risk premia. The market price for risk in cash flows is highly significant. We argue that cash flow risk is important for interpreting differences in risk compensation across assets.