Nonparametric Tail Copula Estimation: An Application to Stock and Volatility Index Returns

DOI10.1080/03610918.2011.650256zbMath1347.62074OpenAlexW2036288595MaRDI QIDQ4921583

Wing Lon Ng, Yuri Salazar

Publication date: 13 May 2013

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2011.650256

zbMATH Keywords

copulaextreme value theorynonparametric estimationtail dependencestockvolatility indices

Mathematics Subject Classification ID

Applications of statistics to actuarial sciences and financial mathematics (62P05) Nonparametric estimation (62G05) Statistics of extreme values; tail inference (62G32)

Uses Software

• QRM

Cites Work

• Rank-based inference for bivariate extreme-value copulas
• Weak convergence of empirical copula processes
• Vine copulas with asymmetric tail dependence and applications to financial return data
• Estimating the tail-dependence coefficient: properties and pitfalls
• Non-parametric Estimation of Tail Dependence
• Nonparametric estimation of the lower tail dependence λ_Lin bivariate copulas
• Dependence measures for extreme value analyses
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