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Dynamic Density Forecasts for Multivariate Asset Returns

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  • Evarist Stoja
  • Arnold Polanski

    ()

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.

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File URL: http://www.efm.bris.ac.uk/economics/working_papers/pdffiles/dp09616.pdf
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Bibliographic Info

Paper provided by Department of Economics, University of Bristol, UK in its series Bristol Economics Discussion Papers with number 09/616.

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Length: 27 pages
Date of creation: Sep 2009
Date of revision:
Handle: RePEc:bri:uobdis:09/616

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Related research

Keywords: Time-varying higher co-moments; Joint Density Forecasting; Method of Moments; Multivariate Value-at-Risk.;

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