Dynamic Density Forecasts for Multivariate Asset Returns

Abstract:     
We propose a simple and flexible framework for forecasting the joint density of asset returns. The multinormal distribution is augmented with a polynomial in (time-varying) non-central co-moments of assets. We estimate the coefficients of the polynomial via the Method of Moments for a carefully selected set of co-moments. In an extensive empirical study, we compare the proposed model with a range of other models widely used in the literature. Employing a recently proposed technique to evaluate multivariate forecasts, we conclude that the augmented joint density provides highly accurate forecasts of the negative tail of the joint distribution.

Number of Pages in PDF File: 26

Keywords: Time-Varying Higher Co-Moments, Joint Density Forecasting, Method of Moments, Multivariate Value-at-Risk

JEL Classification: C22, C51, C52, G11

working papers series