This paper studies market selection in an Arrow-Debreu economy with complete markets where agents learn over misspecified models. Under model misspecification, standard Bayesian learning loses its formal justification and biased learning processes may provide a selection advantage. However,...

We consider a market economy where two rational agents are able to learn the distribution of future events. In this context, we study whether moving away from the standard Bayesian belief updating, in the sense of under-reaction to some degree to new information, may be strategically convenient...

The behavioural finance literature attributes the persistent market misvaluation observed in real data to the presence of deviations from rational thinking of the actors involved. Cognitive biases and the use of simple heuristics can be described using expected utility maximising agents that...

Financial, managerial, and medical decisions often involve alternatives whose possible outcomes have uncertain probabilities. In contrast to alternatives whose probabilities are known, these uncertain alternatives offer the benefits of learning. In repeat-choice situations, such learning brings...

We study an investor's optimal consumption and portfolio choice problem when he is confronted with two possibly misspecified submodels of stock returns: one with IID returns and the other with predictability. We adopt a generalized recursive ambiguity model to accommodate the investor's aversion...

We solve in closed form the optimal consumption / portfolio choice problem for the class of isoelastic utility functions under incomplete information about the mean return of the stock price. Our approach consists in converting the original investor's problem into an equivalent program where the...

The behavioural finance literature attributes the persistent market misvaluation observed in real data to the presence of deviations from rational thinking of the actors involved. Cognitive biases and the use of simple heuristics can be described using expected utility maximising agents that...

This paper proposes a new approach for modeling investor fear after rare disasters. The key element is to take into account that investors' information about fundamentals driving rare downward jumps in the dividend process is not perfect. Bayesian learning implies that beliefs about the...

We consider a market economy where two rational agents are able to learn the distribution of future events. In this context, we study whether moving away from the standard Bayesian belief updating, in the sense of under-reaction to some degree to new information, may be strategically convenient...

Option-based portfolio insurance is a unique solution that combines a downside protection with guaranteed minimum upside participation. Its implementation, however, is challenging for public funds, whose investors have different entry points and uncertain holding periods. In this paper we extend...