Non-parametric estimation of copula parameters: testing for time-varying correlation

DOI10.1515/SNDE-2012-0089zbMath1506.62405OpenAlexW2018522583MaRDI QIDQ2687861

Jinguo Gong, Daimin Shi, Weiou Wu, David G. McMillan

Publication date: 7 March 2023

Published in: Studies in Nonlinear Dynamics and Econometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1515/snde-2012-0089

zbMATH Keywords

stock returnskernel estimatelocal likelihood estimationtime-varying copuladynamic dependence

Mathematics Subject Classification ID

Density estimation (62G07) Applications of statistics to actuarial sciences and financial mathematics (62P05) Measures of association (correlation, canonical correlation, etc.) (62H20) Characterization and structure theory for multivariate probability distributions; copulas (62H05)

Cites Work

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• An introduction to copulas. Properties and applications
• Generalized likelihood ratio statistics and Wilks phenomenon
• Efficient estimation of a semiparametric dynamic copula model
• Copula–Based Models for Financial Time Series
• Local Maximum Likelihood Estimation and Inference
• Efficient Estimation and Inferences for Varying-Coefficient Models
• A semiparametric estimation procedure of dependence parameters in multivariate families of distributions
• Semiparametric estimation in copula models

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