[This paper studies the term structure implications of a simple structural model in which the representative agent displays ambiguity aversion, modeled by Multiple Priors Recursive Utility. Bond excess returns reflect a premium for ambiguity, which is observationally distinct from the risk premium of affine yield curve models. The ambiguity premium can be large even in the simplest log-utility setting and is also nonzero for stochastic factors that have a zero risk premium. A calibrated low-dimensional two-factor model with ambiguity is able to reproduce the deviations from the expectations hypothesis documented in the literature, without modifying in a substantial way the nonlinear mean-reversion dynamics of the short interest rate. Moreover, the model does not imply any apparent trade-off between fitting the first and second moments of the yield curve.]

[In a Lucas exchange economy with standard power utility, we study asset prices under learning and ambiguous information. In contrast with models featuring only learning or ambiguity, our model is successful in matching the equity premium, the interest rate, and the volatility of stock returns under empirically reasonable parameters. Our closed-form formulas also show that a severe downward bias arises in the empirical relation between stock returns and return volatility. We quantify this bias in simulations and show that our model can explain why such a relation is difficult to detect in the data.]

We analyze the empirical predictions of ambiguity aversion in intertemporal heterogenous agents economies. We examine equilibria for two tract able wealth–homothetic settings of ambiguity aversion in continuous time. Each setting is motivated by a different robust control optimization problem. We show that ambiguity aversion affects optimal portfolios in a way that is similar to an increase in risk aversion. A distinct property of our second setting of ambiguity aversion is that this increase is state dependent, highly pronounced at moderate portfolio exposures and reduces equity-market participation. In general equilibrium, ambiguity aversion raises the equity premium and lowers interest rates. A distinct feature of our second setting of ambiguity aversion is that the equity premium part due to ambiguity aversion dominates when volatility is low.

This paper studies the term structure implications of a simple structural model in which the representative agent displays ambiguity aversion, modeled by Multiple Priors Recursive Utility. Bond excess returns reflect a premium for ambiguity, which is observationally distinct from the risk premium of affine yield curve models. The ambiguity premium can be large even in the simplest log-utility setting and is also nonzero for stochastic factors that have a zero risk premium. A calibrated low-dimensional two-factor model with ambiguity is able to reproduce the deviations from the expectations hypothesis documented in the literature, without modifying in a substantial way the nonlinear mean-reversion dynamics of the short interest rate. Moreover, the model does not imply any apparent trade-off between fitting the first and second moments of the yield curve. The Author 2008. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please e-mail: [email protected]., Oxford University Press.

We propose a model-free methodology to estimate international stochastic discount factors (SDFs) that jointly price cross-sections of international stocks, bonds, and currencies in markets with frictions. We theoretically establish a SDF decomposition into one global factor and a currency basket. We show that our global factor prices a large cross-section of international asset returns , not just in- but also out-of-sample, across different currency denominations. Moreover, the pricing ability of the global factor is largely independent of the market structure or the size and type of market friction.

We provide a theoretical framework to uncover in a model‐free way the relationships among international stochastic discount factors (SDFs), stochastic wedges, and financial market structures. Exchange rates are in general different from the ratio of international SDFs in incomplete markets, as captured by a stochastic wedge. We show theoretically that this wedge can be zero in incomplete and integrated markets. Market segmentation breaks the strong link between exchange rates and international SDFs, which helps address salient features of international asset returns while keeping the volatility and cross‐country correlation of SDFs at moderate levels.

In a Lucas exchange economy with standard power utility, we study asset prices under learning and ambiguous information. In contrast with models featuring only learning or ambiguity, our model is successful in matching the equity premium, the interest rate, and the volatility of stock returns under empirically reasonable parameters. Our closed-form formulas also show that a severe downward bias arises in the empirical relation between stock returns and return volatility. We quantify this bias in simulations and show that our model can explain why such a relation is difficult to detect in the data.

Under mild assumptions, we recover the model‐free conditional minimum variance projection of the pricing kernel on various tradeable realized moments of market returns. Recovered conditional moments predict future realizations and give insight into the cyclicality of equity premia, variance risk premia, and the highest attainable Sharpe ratios under the minimum variance probability. The pricing kernel projections are often U ‐shaped and give rise to optimal conditional portfolio strategies with plausible market timing properties, moderate countercyclical exposures to higher realized moments, and favorable out‐of‐sample Sharpe ratios.

We provide novel evidence for an equilibrium link between investors' disagreement, the market price of volatility and correlation, and the differential pricing of index and individual equity options. We show that belief disagreement is positively related to (i) the wedge between index and individual volatility risk premia, (ii) the different slope of the smile of index and individual options, and (iii) the correlation risk premium. Priced disagreement risk also explains returns of option volatility and correlation trading strategies in a way that is robust to the inclusion of other risk factors and different market conditions.

We develop a new framework for multivariate intertemporal portfolio choice that allows us to derive optimal portfolio implications for economies in which the degree of correlation across industries, countries, or asset classes is stochastic. Optimal portfolios include distinct hedging components against both stochastic volatility and correlation risk. We find that the hedging demand is typically larger than in univariate models, and it includes an economically significant covariance hedging component, which tends to increase with the persistence of variance–covariance shocks, the strength of leverage effects, the dimension of the investment opportunity set, and the presence of portfolio constraints.