Estimation of Contagion: Bayesian Model Averaging on Tail Dependence of Mixture Copula

Sundusit Saekow, Phisanu Chiawkhun (), Woraphon Yamaka, Nawapon Nakharutai and Parkpoom Phetpradap
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Sundusit Saekow: Applied Statistics Program, Department of Statistics, Faculty of Science, Chiang Mai University, Chiang Mai 50200, Thailand
Phisanu Chiawkhun: Department of Statistics, Faculty of Science, Chiang Mai University, Chiang Mai 50200, Thailand
Woraphon Yamaka: Faculty of Economic, Chiang Mai University, Chiang Mai 50200, Thailand
Nawapon Nakharutai: Department of Statistics, Faculty of Science, Chiang Mai University, Chiang Mai 50200, Thailand
Parkpoom Phetpradap: Department of Mathematics, Faculty of Science, Chiang Mai University, Chiang Mai 50200, Thailand

Mathematics, 2024, vol. 12, issue 21, 1-23

Abstract: This study introduces a novel approach to estimate tail dependence in financial contagion using mixture copulas. Addressing the challenges of weight parameter estimation in conventional models, we propose a Bayesian model averaging method to determine optimal copula weights. Through both simulations and empirical studies, the proposed method demonstrates improved robustness and accuracy, particularly when handling extreme weight scenarios. These advancements offer more reliable measurements of financial contagion, contributing to enhanced risk management and policy-making in interconnected financial markets.

Keywords: Bayesian model averaging; contagion; copula; tail dependence (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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