Semiparametric Dynamic Max-Copula Model for Multivariate Time Series

DOI10.1111/rssb.12256OpenAlexW2766823937MaRDI QIDQ4607216

Zifeng Zhao, Zhengjun Zhang

Publication date: 13 March 2018

Published in: Journal of the Royal Statistical Society Series B: Statistical Methodology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/rssb.12256

zbMATH Keywords

tail dependenceasymmetric dependencemixture modellingcomposite maximum likelihoodcopula constructionmarket crisis

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to actuarial sciences and financial mathematics (62P05) Characterization and structure theory for multivariate probability distributions; copulas (62H05)

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On studying extreme values and systematic risks with nonlinear time series models and tail dependence measures ⋮ Multivariate extremes and max-stable processes: discussion of the paper by Zhengjun Zhang ⋮ Rejoinder of “On studying extreme values and systematic risks with nonlinear time series models and tail dependence measures” ⋮ New extreme value theory for maxima of maxima ⋮ MULTIVARIATE COMPOSITE COPULAS ⋮ Efficient estimation of multivariate semi-nonparametric GARCH filtered copula models ⋮ Enhanced pricing and management of bundled insurance risks with dependence-aware prediction using pair copula construction ⋮ Inference for Archimax copulas

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