We propose a flexible stochastic framework for modeling the market share dynamics over time in a multiple markets setting, where firms interact within and between markets. Firms undergo stochastic idiosyncratic shocks, which contract their shares, and compete to consolidate their position by...

This paper studies the pricing implications of the sole ambiguity aversion, in a Lucas’ tree economy where asset returns are ambiguous. Abstracting from a specific functional form, we disentangle the model-specific effect from the effect of ambiguity aversion. In addition, we allow the...

The study of properties of mean functionals of random probability measures is an important area of research in the theory of Bayesian nonparametric statistics. Many results are known by now for random Dirichlet means but little is known, especially in terms of posterior distributions, for...

An important issue in survival analysis is the investigation and the modeling of hazard rates. Within a Bayesian nonparametric framework, a natural and popular approach is to model hazard rates as kernel mixtures with respect to a completely random measure. In this paper we provide a...

The present paper provides a review of the results concerning distributional properties of means of random probability measures. Our interest in this topic has originated from inferential problems in Bayesian Nonparametrics. Nonetheless, it is worth noting that these random quantities play an...

This paper axiomatizes an intertemporal version of the Smooth Ambiguity decision model developed in Klibanoff, Marinacci, and Mukerji (2005). A key feature of the model is that it achieves a separation between ambiguity, identified as a characteristic of the decision maker's subjective beliefs,...

We introduce and axiomatize dynamic variational preferences, the dynamic version of the variational preferences we axiomatized in [21], which generalize the multiple priors preferences of Gilboa and Schmeidler [9], and include the Multiplier Preferences inspired by robust control and first used...