We propose a new modeling framework to study the asset pricing implications of learning under ambiguity aversion. In a continuous time partial information Lucas economy, we characterize analytically equilibrium equity returns and make the following observations. First, learning under ambiguity...

We solve analytically the Merton's problem of an investor with timeadditive power utility. For general state dynamics, we prove existence of two power series representations of the relevant optimal policies and value functions, which hold for all admissible risk aversion parameters. We...

We analyze the empirical predictions arising from settings of ambiguity aversion in intertemporal heterogenous agents economies. We study equilibria for two tractable wealth-homothetic settings of ambiguity aversion in continuous time. Such settings are motivated by a different robust control...

We apply perturbation theory to solve the optimal control problem of an investor with time-additive power utility over intermediate consumption and final wealth. Under general conditions we show existence of a power series representation for the prevailing optimal consumption and investment...

The paper presents a robust version of a simple two-assets Merton (1969, Review of Economics and Statistics 51, 247-57) model where the optimal choices and the implied shadow market prices of risk for a representative robust decision maker (RDM) can be easily described. With the exception of the...

We study the partial and general equilibrium implications of value-at-risk (VaR) regulation in continuous-time economies with intermediate expenditure, stochastic opportunity set, and heterogeneous attitudes to risk. Our findings show that because of an anticipatory effect of VaR constraints on...

We analyze and compare analytically continuous-time financial equilibria where heterogeneous risk averse investors care about model misspecification through some preference for robustness and in the presence of a stochastic opportunity set. This incorporates a concern for model misspecification...

We present a geometric approach to discrete time multiperiod mean variance portfolio optimization that largely simplies the mathematical analysis and the economic interpretation of such model settings. We show that multiperiod mean variance optimal policies can be decomposed in an orthogonal set...

We propose a new multivariate DCC-GARCH model that extends existing approaches by admitting multivariate thresholds in conditional volatilities and conditional correlations. Model estimation is numerically feasible in large dimensions and positive semi-definiteness of conditional covariance...

We develop a new framework for intertemporal portfolio choice when the covariance matrix of returns is stochastic. An important contribution of this framework is that it allows to derive optimal portfolio implications for economies in which the degree of correlation across different industries,...