Global Market Shocks and Tail Risk Spillovers: Evidence from a Copula-Based Contagion Framework

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

JRFM, 2025, vol. 18, issue 9, 1-24

Abstract: This study investigates the dynamics of financial contagion using a flexible mixture copula framework, specifically a combination of the Survival Clayton and Survival Gumbel copulas, to estimate the lower tail dependence coefficient, interpreted as a measure of extreme downside co-movement or contagion. The model captures nonlinear and asymmetric dependencies between the global stock market and nine national markets: Australia, China, Hungary, India, New Zealand, Spain, Thailand, the United Kingdom, and the United States. The analysis spans the period from 2018 to 2024 and focuses on three major global crises: the China–U.S. trade war, the COVID-19 pandemic, and the Russia–Ukraine conflict. The results reveal substantial heterogeneity in contagion intensity across countries and crises. The COVID-19 pandemic generated the highest and most synchronized levels of contagion, with tail dependence exceeding 0.8 in the United States and above 0.6 in several developed and emerging markets. The China–U.S. trade war resulted in moderate contagion, particularly in countries with close trade links to the U.S. and China. The Russia–Ukraine conflict produced elevated contagion in European and energy-sensitive markets such as the UK and Spain. Conversely, China and New Zealand exhibited relatively lower levels of contagion across all periods

Keywords: Bayesian model averaging; contagion; copula; tail dependence (search for similar items in EconPapers)
JEL-codes: C E F2 F3 G (search for similar items in EconPapers)
Date: 2025
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