Tail Dependence Measure for Examining Financial Extreme Co-Movements
32 Pages Posted: 9 Jan 2014 Last revised: 16 Aug 2016
Date Written: April 8, 2015
Modeling and forecasting extreme co-movements in financial market is important for conducting stress test in risk management. Asymptotic independence and asymptotic dependence behave drastically different in modeling such co-movements. For example, the impact of extreme events is usually overestimated whenever asymptotic dependence is wrongly assumed. On the other hand, the impact is seriously underestimated whenever the data is misspecified as asymptotic independent. Therefore, distinguishing between asymptotic independence/dependence scenarios is very informative for any decision-making and especially in risk management. We investigate the properties of the limiting conditional Kendall's tau which can be used to detect the presence of asymptotic independence/dependence. We also propose nonparametric estimation for this new measure and derive its asymptotic limit. A simulation study shows good performances of the new measure and its combination with the coefficient of tail dependence proposed by Ledford and Tawn (1996, 1997). Finally, applications to financial and insurance data are provided.
Keywords: Asymptotic dependence and independence; Copula; Extreme co-movement; Kendall's tau; Measure of association.
JEL Classification: C13, C14, C44
Suggested Citation: Suggested Citation