Estimation of Financial Agent-Based Models with Simulated Maximum Likelihood

This paper proposes a general computational framework for empirical estimation of financial agent based models, for which criterion functions do not have known analytical form. For this purpose, we adapt a nonparametric simulated maximum likelihood estimation based on kernel methods. Employing one of the most widely analysed heterogeneous agent models in the literature developed by Brock and Hommes (1998), we extensively test properties of the proposed estimator and its ability to recover parameters consistently and efficiently using simulations. Key empirical findings point us to the statistical insignificance of the switching coefficient but markedly significant belief parameters defining heterogeneous trading regimes with superiority of trend-following over contrarian strategies. In addition, we document slight proportional dominance of fundamentalists over trend following chartists in main world markets

Numerical implementation of absorbing and injecting boundary conditions for the time-dependent Schrodinger-equation

Cataloged from PDF version of article.A method is described that enables the absorption and injection of wave functions at the boundaries of a region in a numerical solution to the time-dependent Schrödinger equation. A number of results corresponding to one- and two-dimensional simulations are presented. Such boundary conditions enable the use of time-dependent simulations of geometries connected to contacts that correspond to sources and sinks of particles in thermal equilibrium. The approach presented has a number of attractive features from a numerical-implementation point of view. © 1995 The American Physical Society