The Gaussian Mixture Dynamic Conditional Correlation Model: Parameter Estimation, Value at Risk Calculation, and Portfolio Selection

DOI10.1198/JBES.2009.07238zbMath1202.91346OpenAlexW2011090480MaRDI QIDQ3063006

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Publication date: 30 December 2010

Published in: Journal of Business & Economic Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1198/jbes.2009.07238

zbMATH Keywords

maximum likelihood estimationBayesian inferenceportfolio selectionGaussian mixture modelvalue at riskmultivariate generalized autoregressive conditional heteroscedasticity model

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Statistical methods; risk measures (91G70) Portfolio theory (91G10)

Related Items (4)

A Bayesian non-parametric approach to asymmetric dynamic conditional correlation model with application to portfolio selection ⋮ On variable ordination of modified Cholesky decomposition for estimating time‐varying covariance matrices ⋮ Bayesian semiparametric multivariate GARCH modeling ⋮ A semiparametric Bayesian approach to the analysis of financial time series with applications to value at risk estimation

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