In this paper we argue that in realistically calibrated two period general equilibrium models with incomplete markets CAPM-pricing provides a good benchmark for equilibrium prices even when agents are not mean-variance optimizers and returns are not normally distributed. We numerically...

This paper presents a new sequential method for constrained non-linear optimization problems.The principal characteristics of these problems are very time consuming function evaluations and the absence of derivative information. Such problems are common in design optimization, where time...

In this paper, several problem reduction techniques are discussed that can be used to reduce the solution time of set partitioning problems. These techniques can be applied in any solution algorithm for set partitioning problems. Besides a short review of the existing literature on preprocessing...

Abstract: In this note we generalize a numerical algorithm presented in [9] to calculate all solutions of the scalar algebraic Riccati equations that play an important role in finding feedback Nash equilibria of the scalar N-player linear affine-quadratic differential game. The algorithm is...

AMS classifications: 47H10; 54H25; 55M20; 90C33; 91B50

AMS classifications: 47H10; 54H25; 55M20; 90C26; 90C33; 91B50;

Tucker's well-known combinatorial lemma states that for any given symmetric triangulation of the n-dimensional unit cube and for any integer labeling that assigns to each vertex of the triangulation a label from the set f§1;§2; ¢ ¢ ¢ ;§ng with the property that antipodal vertices on the...

In this paper we study the existence problem of a zero point of a function defined on a finite set of elements of the integer lattice Zn of the n-dimensional Euclidean space IRn. It is assumed that the set is integrally convex, which implies that the convex hull of the set can be subdivided in...

AMS classifications: 90C33, 90C26, 91B50.

In this paper we analyze different schemes for obtaining gradient estimates when the underlying function is noisy.Good gradient estimation is e.g. important for nonlinear programming solvers.As an error criterion we take the norm of the difference between the real and estimated gradients.This...