Conditional empirical copula processes and generalized dependence measures

2020/08/21 by Alexis Derumigny, Derumigny, Alexis, Jean-David Fermanian +2 · 1 citation
Economics, Econometrics and Finance · Mathematics · #62G05 #62G09 (Secondary) #62G30 (Primary) 62H20 #FOS: Mathematics #Financial Risk and Volatility Modeling #Statistical Methods and Inference #Statistics Theory (math.ST) #Stochastic processes and financial applications #math.ST #msc:62G05 #msc:62G09 #msc:62G30 #msc:62H20 #stat.TH

paper · pdf · doi:10.48550/arxiv.2008.09480

29 pages, 4 figures

arxiv created 2020/08/21 · openalex publication_date 2020/08/21 · arxiv updated 2020/08/24 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

We study the weak convergence of conditional empirical copula processes, when the conditioning event has a nonzero probability. The validity of several bootstrap schemes is stated, including the exchangeable bootstrap. We define general - possibly conditional - multivariate dependence measures and their estimators. By applying our theoretical results, we prove the asymptotic normality of some estimators of such dependence measures.

Citations

• ON THE METHOD OF PAIRED COMPARISONS
• MODELLING ASYMMETRIC EXCHANGE RATE DEPENDENCE*

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• The Strong, Weak and Benign Goodhart's law. An independence-free and paradigm-agnostic formalisation

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