Dynamic Density Forecasts for Multivariate Asset Returns

Arnold Polanski, Evarist Stoja

Research output: Contribution to journalArticle

1 Citation (Scopus)

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 as well as standard techniques to evaluate multivariate forecasts, we conclude that the augmented joint density provides highly accurate forecasts of the “negative tail” of the joint distribution.
Original languageEnglish
Pages (from-to)523-540
Number of pages18
JournalJournal of Forecasting
Volumex
Issue number6
Publication statusPublished - Sep 2011

ASJC Scopus subject areas

  • Strategy and Management
  • Computer Science Applications
  • Management Science and Operations Research
  • Statistics, Probability and Uncertainty
  • Modelling and Simulation

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  • Cite this

    Polanski, A., & Stoja, E. (2011). Dynamic Density Forecasts for Multivariate Asset Returns. Journal of Forecasting, x(6), 523-540.