A general formalism on stochastic choice is presented. Tje Rationalizability and Recoverability (Identification) problems are discussed. For the identification issue parametric examples are analyzed by means of techniques of mathematical tomography (Random transforms)

This paper proposes an auxiliary particle filter algorithm for inference in regime switching stochastic volatility models in which the regime state is governed by a first-order Markov chain. We proposes an ongoing updated Dirichlet distribution to estimate the transition probabilities of the...

We study the consumption behaviour of an asymmetric network of heterogeneous agents in the framework of discrete choice models with stochastic decision rules. We assume that the interactions among agents are uniquely specified by their "social distance" and consumption is driven by peering,...

Experimental work regularly finds that individual choices are not rationalized. Nonetheless, recent work shows that data collected from many individuals can be stochastically rationalized by a distribution of well-defined preferences. We study the relationship between deterministic and...

We show that a steeply increasing workload before a deadline is compatible with time-consistent preferences. The key departure from the literature is that we consider a stochastic environment where success of effort is not guaranteed

In this paper we consider the pricing of an American call option whose underlying asset dynamics evolve under the influence of two independent stochastic volatility processes of the Heston (1993) type. We derive the associated partial differential equation (PDE) of the option price using hedging...

In this paper we consider the pricing of an American call option whose underlying asset dynamics evolve under the influence of two independent stochastic volatility processes as proposed in Christoffersen, Heston and Jacobs (2009). We consider the associated partial differential equation (PDE)...

We show that a steeply increasing workload before a deadline is compatible with time-consistent preferences. The key departure from the literature is that we consider a stochastic environment where success of effort is not guaranteed. -- Increasing Workload ; Deadline ; Stochasticity