Multivariate affine generalized hyperbolic distributions: An empirical investigation
The aim of this paper is to estimate multivariate affine generalized distributions (MAGH) using market data. We use the Ibovespa, CAC, DAX, FTSE, NIKKEI and S&P500 indexes. We estimate the univariate distributions, bi-variate distributions and six-dimensional distribution. Then we assess their goodness of fit using Kolmogorov distances. As an application we study the efficient frontier.
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- Fajardo, José & Farias, Aquiles, 2004.
"Generalized Hyperbolic Distributions and Brazilian Data,"
Brazilian Review of Econometrics,
Sociedade Brasileira de Econometria - SBE, vol. 24(2), November.
- José Fajardo & Aquiles Farias, 2002. "Generalized Hyperbolic Distributions and Brazilian Data," Working Papers Series 52, Central Bank of Brazil, Research Department.
- Fajardo, J. & Farias, A., 2003. "Generalized Hyperbolic Distributions and Brazilian Data," Finance Lab Working Papers flwp_57, Finance Lab, Insper Instituto de Ensino e Pesquisa.
- Fajardo, J. & Farias, A. R. & Ornelas, J. R. H., 2003. "Analyzing the Use of Generalized Hyperbolic Distributions to Value at Risk Calculations," Finance Lab Working Papers flwp_58, Finance Lab, Insper Instituto de Ensino e Pesquisa.
- repec:sbe:breart:v:21:y:2001:i:2:a:2752 is not listed on IDEAS
- Schmidt, Rafael & Hrycej, Tomas & Stutzle, Eric, 2006. "Multivariate distribution models with generalized hyperbolic margins," Computational Statistics & Data Analysis, Elsevier, vol. 50(8), pages 2065-2096, April. Full references (including those not matched with items on IDEAS)