We study the intertemporal utility maximization problem for Hindy-Huang-Kreps utilities. Necessary and sufficient conditions for optimality are given. An explicit solution is provided for a large class of utility functions. In particular, the case of separable power utilities with a finite time...

The utility maximization problem of "ratchet investors" who do not tolerate any decline in their consumption rate is solved explicitly for all felicity functions in a Markovian framework which includes Brownian motion and Poisson processes as special cases. The optimal consumption plan turns out...

We extend the analysis of the intertemporal utility maximization problem for Hindy-Huang-Kreps utilities reported in Bank and Riedel (1998) to the stochastic case. Existence and uniqueness of optimal consumption plans are established under arbitrary convex portfolio constraints, including both...

We prove existence of an Arrow-Debreu equilibrium when agents' preferences exhibit local substitution in the sense of Hindy, Huang, and Kreps (1992). Efficient allocations and supporting price functionals are identified and characterized. Under Hindy Huang Kreps preferences, equilibrium price...

Problems arising in Finance have become a significant source of new developments in Stochastic Analysis. We discuss some recent case studies, in particular some decomposition and representation theorems which are motivated by problems of hedging derivatives and of intertemporal consumption choice.

East-West migration in Germany peaked at the beginning of the 90s although the average wage gap between Eastern and Western Germany continues to average about 25%. We analyze the propensity to migrate using microdata from the German Socioeconomic Panel. Fitting a parametric Generalized Linear...

We show in the paper that the decomposition proposed by Beveridge and Nelson (1981) for models that are integrated of order one can be generalized to seasonal Arima models by means of a partial fraction decomposition. Two equivalent algorithms are proposed to optimally (in the mean squared...