Endnote export
%T Gram-Charlier densities: A multivariate approach %A Brio, Esther B. del %A Niguez, Trino-Manuel %A Perote, Javier %J Quantitative Finance %N 7 %P 855-868 %V 9 %D 2009 %K Empirical finance; Econometrics of financial markets; Financial assets; VaR; Financial Econometrics; Non-Gaussian Distributions; GARCH models; Forecasting Ability; Risk Management; Asymmetry %= 2011-03-14T14:45:00Z %~ http://www.peerproject.eu/ %> https://nbn-resolving.org/urn:nbn:de:0168-ssoar-221490 %X 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. %C GBR %G en %9 journal article %W GESIS - http://www.gesis.org %~ SSOAR - http://www.ssoar.info