A0375
Title: Consistent estimation of multiple breakpoints in dependence measures
Authors: Marvin Borsch - Institut for Okonometrie und Statistik (Germany) [presenting]
Alexander Mayer - Universita Ca Foscari Venezia (Italy)
Dominik Wied - University of Cologne (Germany)
Abstract: Different methods are proposed to consistently detect multiple breaks in copula-based dependence measures. We allow for breaks in multiple and grouped dependence measures. Starting with the classical binary segmentation, also the more recent wild binary segmentation (WBS) is considered. For binary segmentation, consistency of the estimators for the location of the breakpoints as well as the number of breaks is proved, taking filtering effects from AR-GARCH models explicitly into account. Monte Carlo simulations based on a factor copula as well as on a Clayton copula model illustrate the strengths and limitations of the procedures. A real data application on recent Euro Stoxx 50 data considering the COVID-19 pandemic reveals some interpretable breaks in the dependence structure.
