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 study the optimal policies and mean-variance frontiers (MVF) of a multiperiod mean-variance optimization of assets and liabilities (AL). Our model allows for a contemporaneous optimization of the balance-sheet as a whole. This makes the analysis more challenging than in a setting based on...

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 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...

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...