# Measuring contagion risk in high volatility state among Taiwanese major banks

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## Abstract

This paper studies the structural tail dependence and contagion risk especially in high volatility state between domestic (Taiwanese) and foreign banks. Aptly the two-state threshold copula GARCH provides the threshold regression and copulas to classify the actual volatility index into a high or in a low state and estimate the structural tail dependences using Kendall taus to probe the co-movement among banks. In high volatility state, the average Kendall taus and value at risk as well as expected shortfall are about two times larger than in low volatility state. The asymmetric jumps of Kendall taus appear more frequent in the subprime crisis whereas the symmetric trends of Kendall taus appear higher in Greek debt crisis. Among three copula models in low volatility state, Gaussian and Student-t copula models have established a more significant estimate than the Clayton copula model. However, in high volatility state, Clayton copula model could still produce an acceptable estimate. Empirically, using Clayton copula in high volatility state has demonstrated clearly intensive tail jumps capable to distinguish the contagion risk.

## Keywords

Contagion risk Threshold GARCH Copula Tail dependence## Notes

### Acknowledgements

The author wants to express great appreciation to Dr. Thomas W. Knowles (Emeritus Professor of IIT Stuart School of Business in Chicago), Dr. Arch G. Woodside (Professor of Marketing of Wallace E. Carroll School of Management at Boston College), and Dr. Sheng-Jung Li (Assistant Professor of Finance Department at Shu-Te University in Kaohsiung) for their constructive comments and insights and deeply thankful to the support of The Ministry of Science and Technology of the Republic of China for the grant of research funding.

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