Krylov subspace methods have proven to be powerful methods for solving sparse linear systems arising in several engineering problems. More recently, these methods have been successfully applied in computational economics, for instance in the solution of forward-looking macroeconometric models...

Many numerical methods to price options have been suggested in the finance literature. This paper aims at reviewing several numerical approaches in order to discuss their practical strenghts and/or weaknesses. The problem under investigation is a multivariate contingent claims model with three...

Monte Carlo (MC) methods have proved flexible, robust and very useful techniques in computational finance. Several studies have investigated ways to achieve greater efficiency for such methods for serial computers.In this paper, we concentrate on the parallelization potentials of the MC methods....

In this paper we present an implementation of a Newton method based on iterative Krylov subspace methods such as GMRES, QMR and BiCGSTAB for solving large nonlinear macroeconometric models. These methods are tested for the solution of the model MULTIMOD and the computational costs of the...

This paper presents a dynamic model of job search behavior over the Life Cycle. Individuals endogenously make consumption-saving, labor-leisure, and search decisions under capital, lifetime and wage uncertainty. We extend recent research on these types of stochastic dynamic programming models to...