An EPMS Price Estimator for Multi-Asset Financial Derivatives

Abstract

This study proposes an empirical P-martingale simulation (EPMS) price estimator of multi-asset financial derivatives. Under mild assumptions on the payoff functions, the strong consistency and asymptotic normality of the proposed estimator are established. Several simulation scenarios are conducted to investigate the performance of the proposed price estimator under multivariate geometric Brownian motion and multivariate GARCH models. Numerical results indicate that the multi-asset EPMS price estimator is capable of improving the efficiency of the standard Monte Carlo price estimator. In addition, the asymptotic distribution serves as a persuasive approximation for samples consisting of as few as 500 simulation paths, which helps to reduce the computation time of finding confidence intervals for the prices of multi-asset derivatives.