TY  - CHAP
AB  - Tail-dependence evolution for the symmetrized Joe–Clayton copula is proposed to depend on an exponentially weighted moving average (EWMA) of the absolute difference in probability integral transforms. Using these dynamics, time-varying tail dependence between bank and insurance equity prices is assessed in a parametric copula, generalized autoregressive conditional heteroscedastic framework. The results suggest a relatively long lag and support the EWMA lag structure as an effective estimation vehicle. Tail dependence is shown often to tend higher during periods of market stress.
VL  - 30
SN  - 978-1-78190-309-4, 978-1-78190-310-0/0731-9053
DO  - 10.1108/S0731-9053(2012)0000030018
UR  - https://doi.org/10.1108/S0731-9053(2012)0000030018
AU  - Chen Jiaqi
AU  - Gunther Jeffery W.
ED  - Dek Terrell
ED  - Daniel Millimet
PY  - 2012
Y1  - 2012/01/01
TI  - Copula–GARCH Time-Varying Tail Dependence
T2  - 30th Anniversary Edition
T3  - Advances in Econometrics
PB  - Emerald Group Publishing Limited
SP  - 411
EP  - 425
Y2  - 2024/04/25
ER  -