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Gram-Charlier densities : A multivariate approach

[journal article]

Brio, Esther B. del; Niguez, Trino-Manuel; Perote, Javier

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Please use the following Persistent Identifier (PID) to cite this document:http://nbn-resolving.de/urn:nbn:de:0168-ssoar-221490

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Abstract This paper introduces a new family of multivariate distributions based on Gram-Charlier and Edgeworth expansions. This family encompasses many of the univariate semi-nonparametric densities proposed in financial econometrics as marginal of its different formulations. Within this family, we focus on the analysis of the specifications that guarantee positivity to obtain well-defined multivariate semi-nonparametric densities. We compare two different multivariate distributions of the family with the multivariate Edgeworth-Sargan, Normal, Student's t and skewed Student's t in an in- and out-sample framework for financial returns data. Our results show that the proposed specifications provide a quite reasonably good performance being so of interest for applications involving the modelling and forecasting of heavy-tailed distributions.
Classification Economic Statistics, Econometrics, Business Informatics
Free Keywords Empirical finance; Econometrics of financial markets; Financial assets; VaR; Financial Econometrics; Non-Gaussian Distributions; GARCH models; Forecasting Ability; Risk Management; Asymmetry
Publication Year 2009
Page/Pages p. 855-868
Journal Quantitative Finance, 9 (2009) 7
DOI http://dx.doi.org/10.1080/14697680902773611
Status Postprint; peer reviewed
Licence PEER Licence Agreement (applicable only to documents from PEER project)