Back to Search
Start Over
Gram-Charlier densities: A multivariate approach
- Source :
- Quantitative Finance
- Publication Year :
- 2009
- Publisher :
- GBR, 2009.
-
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-non-parametric 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-non-parametric 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-of-sample framework for financial returns data. Our results show that the proposed specifications provide a reasonably good performance, and would therefore be of interest for applications involving the modelling and forecasting of heavy-tailed distributions.
- Subjects :
- Multivariate statistics
Economics
Autoregressive conditional heteroskedasticity
Univariate
Wirtschaft
Empirical finance
Econometrics of financial markets
Financial assets
VaR
Financial Econometrics
Non-Gaussian Distributions
GARCH models
Forecasting Ability
Risk Management
Asymmetry
Multivariate analysis of variance
Statistics
Wirtschaftsstatistik, Ökonometrie, Wirtschaftsinformatik
Econometrics
ddc:330
Multivariate t-distribution
Financial econometrics
General Economics, Econometrics and Finance
Finance
Economic Statistics, Econometrics, Business Informatics
Gram
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- Quantitative Finance
- Accession number :
- edsair.doi.dedup.....94ccbde3e76fdf15c547c3c10015d31d