This article successively introduces variable velocity, durability, and habit persistence in a standard two-country general equilibrium model and explores their effects on the variability of exchange rate changes, forward premiums, and the foreign exchange risk premium. A new feature of the model is that agents make decisions at a weekly frequency and face conditionally heteroskedastic shocks. Nevertheless, even the most complex model fails to deliver sufficiently variable risk premiums without causing forward premiums and exchange rates to be excessively variable. Unlike previous models, the model can roughly match the persistence of forward premiums.

We decompose long-term nominal bond yields into real and inflation components in an international context using inflation-linked and nominal bonds. In contrast to extant results, real rate variation dominates the variation in inflation-linked and nominal yields. Cross-country nominal and inflation-linked yield correlations have declined since the Great Recession. Real rates are the main source of the correlation between nominal yields. Our results are robust to various alternative measurements of inflation expectations and the liquidity premium. They continue to hold when a no-arbitrage term structure model with real, nominal, and inflation factors is used to effect the yield decomposition.

Gallant, Hansen, and Tauchen (1990) show how to use conditioning information optimally to construct a sharper unconditional variance bound (the GHT bound) on pricing kernels. The literature predominantly resorts to a simple but suboptimal procedure that scales returns with predictive instruments and computes standard bounds using the original and scaled returns. This article provides a formal bridge between the two approaches. We propose an optimally scaled bound that coincides with the GHT bound when the first and second conditional moments are known. When these moments are misspecified, our optimally scaled bound yields a valid lower bound for the standard deviation of pricing kernels, whereas the GHT bound does not. We illustrate the behavior of the bounds using a number of linear and nonlinear models for consumption growth and bond and stock returns. We also illustrate how the optimally scaled bound can be used as a diagnostic for the specification of the first two conditional moments of asset returns. Copyright 2004, Oxford University Press.

Building on intuition from the dynamic asset pricing literature, we uncover unobserved risk aversion and fundamental uncertainty from the observed time series of the variance premium and the credit spread while controlling for the conditional variance of stock returns, expectations about the macroeconomic outlook, and interest rates. We apply this methodology to monthly data from both Germany and the US. We find that the variance premium contains a substantial amount of information about risk aversion whereas the credit spread has a lot to say about uncertainty. We link our risk aversion and uncertainty estimates to practitioner and “academic” risk aversion indices, sentiment indices, financial stress indices, business cycle indicators and liquidity measures.

We introduce a “bad environment–good environment” (BEGE) technology for consumption growth in a consumption-based asset pricing model with external habit formation. The model generates realistic non-Gaussian features of consumption growth and fits standard salient features of asset prices including the means and volatilities of equity returns and a low risk-free rate. BEGE dynamics additionally allow the model to generate realistic properties of equity index options prices and their comovements with the macroeconomic outlook. In particular, when option-implied volatility is high—as measured, for instance, by the VIX index—the distribution of consumption growth is more negatively skewed.

We use non-Gaussian features in U.S. macroeconomic data to identify aggregate supply and demand shocks while imposing minimal economic assumptions. Macro risks represent the variables that govern the time-varying variance, skewness, and higher-order moments of these two shocks, with ”good” (”bad”) variance associated with positive (negative) skewness. We document that macro risks significantly contribute to the variation of yields and risk premiums for nominal bonds. While overall bond risk premiums are countercyclical, an increase in aggregate demand variance significantly lowers risk premiums. Macro risks also significantly predict future realized bond return variances.

We study a new class of unconditional and conditional mean-variance spanning tests that exploits the duality between Hansen-Jagannathan bounds (1991) and mean-standard deviation frontiers. The tests are shown to be equivalent to standard spanning tests in population, but we document substantial differences in the small sample performance of alternative tests. Our empirical application examines the diversification benefits from emerging equity markets using an extensive new data set on U.S. and U.K.-traded closed-end funds. We find significant diversification benefits for the U.K. country funds, but not for the U.S. funds. The difference appears to relate to differences in portfolio holdings rather than to the behavior of premiums in the United States versus the United Kingdom.

The paper characterizes predictable components in excess rates of returns on major equity and foreign exchange markets using lagged excess returns, dividend yields, and forward premiums as instruments. Vector autoregressive techniques demonstrate one-step-ahead predictability and provide implied long-horizon statistics. We estimate latent variable models as constrained counterparts to the VARs. The predictability of returns is related to asset pricing models by examining the volatility bounds on intertemporal marginal rates of substitution.

ABSTRACT The paper first characterizes the predictable components in excess rates of returns on major equity and foreign exchange markets using lagged excess returns, dividend yields, and forward premiums as instruments. Vector autoregressions (VARs) demonstrate one‐step‐ahead predictability and facilitate calculations of implied long‐horizon statistics, such as variance ratios. Estimation of latent variable models then subjects the VARs to constraints derived from dynamic asset pricing theories. Examination of volatility bounds on intertemporal marginal rates of substitution provides summary statistics that quantify the challenge facing dynamic asset pricing models.

We examine the predictive power of the dividend yields for forecasting excess returns, cash flows, and interest rates. Dividend yields predict excess returns only at short horizons together with the short rate and do not have any long-horizon predictive power. At short horizons, the short rate strongly negatively predicts returns. These results are robust in international data and are not due to lack of power. A present value model that matches the data shows that discount rate and short rate movements play a large role in explaining the variation in dividend yields. Finally, we find that earnings yields significantly predict future cash flows. (JEL C12, C51, C52, E49, F30, G12)