We investigate the relation between returns on stock indices and their corresponding futures contracts to evaluate potential explanations for the pervasive yet anomalous evidence of positive, short-horizon portfolio autocorrelations. Using a simple theoretical framework, we generate empirical implications for both microstructure and partial adjustment models. The major findings are (i) return autocorrelations of indices are generally positive even though futures contracts have autocorrelations close to zero, and (ii) these autocorrelation differences are maintained under conditions favorable for spot-futures arbitrage and are most prevalent during low-volume periods. These results point toward microstructure-based explanations and away from explanations based on behavioral models.

The forward premium anomaly (exchange rate changes are negatively related to interest rate differentials) is one of the most robust puzzles in financial economics. We recast the underlying parity relation in terms of lagged forward interest rate differentials, documenting a reversal of the anomalous sign on the coefficient in the traditional specification. We show that this novel evidence is consistent with recent empirical models of exchange rates that imply exchange rate changes depend on two key variables: the interest rate differential and the magnitude of the deviation of the current exchange rate from that implied by purchasing power parity.

We provide a formal test of the liquidity preference hypothesis (LPH), that is, the monotonicity of ex ante term premiums, using nonparametric estimates that do not require a structural model for conditional expected returns. Although the point estimates of the term premiums are consistent with previous conclusions in the literature regarding violations of the LPH, the test statistics are generally insignificant, even when powerful conditioning information is used. These results illustrate the importance of correctly accounting for correlations across maturities and of formally testing the inequality restrictions implied by the LPH.

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.

This article reexamines the autocorrelation patterns of short-horizon stock returns. We document empirical results which imply that these autocorrelations have been overstated in the existing literature. Based on several new insights, we provide support for a market efficiency-based explanation of the evidence. Our analysis suggests that institutional factors are the most likely source of the autocorrelation patterns.

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.

We investigate the cross-sectional relation between industry-sorted stock returns and expected inflation, and we find that this relation is linked to cyclical movements in industry output. Stock returns of noncyclical industries tend to covary positively with expected inflation, while the reverse holds for cyclical industries. From a theoretical perspective, we describe a model that captures both (i) the cross-sectional variation in these relations across industries, and (ii) the negative and positive relation between stock returns and inflation at short and long horizons, respectively. The model is developed in an economic environment in which the spirit of the Fisher model is preserved.

We investigate the cross‐sectional relation between industry‐sorted stock returns and expected inflation, and we find that this relation is linked to cyclical movements in industry output. Stock returns of noncyclical industries tend to covary positively with expected inflation, while the reverse holds for cyclical industries. From a theoretical perspective, we describe a model that captures both (i) the cross‐sectional variation in these relations across industries, and (ii) the negative and positive relation between stock returns and inflation at short and long horizons, respectively. The model is developed in an economic environment in which the spirit of the Fisher model is preserved.

The behavioral finance literature cites the frozen concentrated orange juice (FCOJ) futures market as a prominent example of the failure of prices to reflect fundamentals. In contrast, we show that when theory clearly identifies the fundamental, e.g., at temperatures close to or below freezing, a close link exists between FCOJ prices and that fundamental. Using a simple, theoretically motivated, nonlinear, state dependent model, we can explain approximately 50% of the return variation on days with freezing temperatures. Moreover, while these observations represent less than 4.5% of the winter sample, they account for two-thirds of the entire winter return variability.

This paper develops tests of inequality restrictions implied by conditional asset pricing models. The methodology is easy to implement, requires little knowledge of the conditional distribution of asset returns, and is valid under fairly weak assumptions. As an application, we test whether the ex ante risk premium is always positive. We report reliable evidence that the ex ante risk premium is negative in some states of the world; these states are related to periods of high expected inflation and especially to downward-sloping term structures.