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Multivariate semi-nonparametric distributions with dynamic conditional correlations

Níguez, Trino Manuel and Del Brio, Esther B. and Perote, Javier (2011) Multivariate semi-nonparametric distributions with dynamic conditional correlations. International Journal of Forecasting, 27 (2). pp. 347-364. ISSN 0169-2070

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Official URL: http://dx.doi.org/10.1016/j.ijforecast.2010.02.005

Abstract

This paper generalizes the Dynamic Conditional Correlation (DCC) model of Engle (2002), incorporating a flexible non-Gaussian distribution based on Gram-Charlier expansions. The resulting semi-nonparametric-DCC (SNP-DCC) model allows estimation in two stages and deals with the negativity problem which is inherent in truncated SNP densities. We test the performance of a SNP-DCC model with respect to the (Gaussian)-DCC through an empirical application of density forecasting for portfolio returns. Our results show that the proposed multivariate model provides a better in-sample fit and forecast of the portfolio returns distribution, and thus is useful for financial risk forecasting and evaluation.

Item Type:Article
Research Community:University of Westminster > Westminster Business School
ID Code:7598
Deposited On:23 Feb 2010 09:41
Last Modified:01 Nov 2012 15:30

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