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

Autor:	Sundusit Saekow, Phisanu Chiawkhun, Woraphon Yamaka, Nawapon Nakharutai, Parkpoom Phetpradap
Jazyk:	angličtina
Rok vydání:	2024
Předmět:	Bayesian model averaging contagion copula tail dependence Mathematics QA1-939
Zdroj:	Mathematics, Vol 12, Iss 21, p 3350 (2024)
Druh dokumentu:	article
ISSN:	2227-7390
DOI:	10.3390/math12213350
Popis:	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.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/e8ca96bd07b0489aaef7101f2bb8a86f Zobrazit plný text záznamu View record in DOAJ Plný text ve formátu PDF Plný text ve formátu HTML
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