We propose a decomposition method for the solution of a dynamic portfolio optimization problem which fits the formulation of a multistage stochastic programming problem. The method allows to obtain time and nodal decomposition of the problem in its arborescent formulation applying a discrete...

In this paper we study the continuous time optimal portfolio selection problem for an investor with a finite horizon who maximizes expected utility of terminal wealth and faces transaction costs in the capital market. It is well known that, depending on a particular structure of transaction...

Many economic models are completed by finding a parameter vector that optimizes a function f, a task that only be accomplished by iterating from a starting vector. Use of a generic iterative optimizer to carry out this task can waste enormous amounts of computation when applied to a class of...

We derive discrete markov chain approximations for continuous state equilibrium term structure models. The states and transition probabilities of the markov chain are chosen effciently according to a quadrature rule as in Tauchen and Hussey (1991). Quadrature provides a simple yet method which...

This paper extends the standard Real Business Cycle model to incorporate sectoral shifts in unemployment. Using relative sectoral technology and sectoral tastes shocks, combined with labor adjustment costs across sectors, we assess the possibility of generating persistent aggregate unemployment....

We consider solutions to general linear dynamic systems, possibly singular and non square with general stability conditions. Besides constructing a general algorytm for finding solutions we provide necessary and sufficient conditions for existence of a solution.

We consider linear dynamic models with rational expectations in case of incomplete and asymmetric information as well as agents heterogeneity. This problem requires solving infinite dimensional matrix equations. We propose asymptotic expansion method to reduce this problem to the finite...

This paper introduces a nonparametric binary classification tree approach to inferring unobserved strategies from the observed actions of economic agents. The strategies are in the form of possibly nested if- then statements. We apply our approach to experimental data from the repeated ultimatum...

This paper considers the relationship between agent-based modeling and economic decision-making experiments with human subjects. Both approaches exploit controlled ``laboratory'' conditions as a means of isolating the sources of aggregate phenomena. Research findings from laboratory studies of...