Recent empirical evidence suggests that expected stock returns are weakly, or even negatively, related to the volatility of stock returns at the market level, and that this relation varies substantially over time. This evidence contradicts the apparently reliable intuition that risk and return are positively related and that stock market volatility is a good proxy for risk. This paper investigates the relation between volatility and expected returns in a general equilibrium, exchange economy. A relatively simple model, estimated using aggregate consumption data, is able to duplicate the salient features of the observed expected return/volatility relation. The key features of the model are the existence of two regimes with different consumption growth processes and time-varying correlations between stock returns and the marginal rate of substitution; thus inducing variability in the short-run relation between expected returns and volatility and a weakening of the long-run relation. These results highlight the perils of relying on intuition from static models. They also have important implications for the empirical modeling of returns.

Evidence of excessive comovement among stocks following index additions (Barberis, Shleifer, and Wurgler, 2005) and stock splits (Green and Hwang, 2009) challenges traditional finance theory. We show that the bivariate regressions in this literature provide little information about the economic magnitude of excess comovement, with coefficients that are sensitive to unrelated factors. Using robust univariate regressions and matched control samples, almost all evidence of excess comovement disappears. In both examples, the stocks exhibit strong returns prior to the event, akin to momentum winners. We document that winner stocks exhibit increases in betas, generating much of the apparent excess comovement.

The prevailing view in finance is that the evidence for long-horizon stock return predictability is significantly stronger than that for short horizons. We show that for persistent regressors, a characteristic of most of the predictive variables used in the literature, the estimators are almost perfectly correlated across horizons under the null hypothesis of no predictability. For example, for the persistence levels of dividend yields, the analytical correlation is 99% between the 1-and 2-year horizon estimators and 94% between the 1-and 5-year horizons, due to the combined effects of overlapping returns and the persistence of the predictive variable. Common sampling error across equations leads to ordinary least squares coefficient estimates and R2s that are roughly proportional to the horizon under the null hypothesis. This is the precise pattern found in the data. The asymptotic theory is corroborated, and the analysis extended by extensive simulation evidence. We perform joint tests across horizons for a variety of explanatory variables, and provide an alternative view of the existing evidence.

There is ongoing debate about the apparent weak or negative relation between risk (conditional variance) and expected returns in the aggregate stock market. We develop and estimate an empirical model based on the intertemporal capital asset pricing model (ICAPM) that separately identifies the two components of expected returns, namely, the risk component and the component due to the desire to hedge changes in investment opportunities. The estimated coefficient of relative risk aversion is positive, statistically significant, and reasonable in magnitude. However, expected returns are driven primarily by the hedge component. The omission of this component is partly responsible for the existing contradictory results.

Multivariate density estimation (MDE) suggests that mortgage-backed security (MBS) prices can be well described as a function of the level and slope of the term structure. We analyze how this function varies across MBSs with different coupons. An important finding is that the interest rate level proxies for the moneyness of the option, the expected level of prepayments, and the average life of the cash flows, while the term structure slope controls for the average rate at which these cash flows should be discounted. Though the origination and prepayment behavior of mortgages differ substantially across coupons, there remains an unexplained common factor in MBS prices. This factor does not seem to be related to the usual suspects and therefore presents a puzzle to financial economists.

This article provides an analytical solution to the problem of an institution optimally managing the market risk of a given exposure by minimizing its Value‐at‐Risk using options. The optimal hedge consists of a position in a single option whose strike price is independent of the level of expense the institution is willing to incur for its hedging program. This optimal strike price depends on the distribution of the asset exposure, the horizon of the hedge, and the level of protection desired by the institution. Moreover, the costs associated with a suboptimal choice of exercise price are economically significant.