To join this seminar virtually: Please request Zoom connection details from ea@stat.ubc.ca
Abstract: In complex systems such as financial networks, the failure of a single entity can trigger cascading effects that threaten the stability of the entire system, and this is known as the systemic risk. A common measure for quantifying systemic risk is CoVaR, the Value-at-Risk of the system conditional on the distress of a single component.
In this talk, I will present a new approach to CoVaR based on tail expansions of copulas. Tail expansions of copulas provide a systematic way to characterize the joint tail behavior of multiple dependent random variables. This characterization naturally integrates and extends classical extreme value theory, offering a more flexible and interpretable representation of extremal dependence.
I will highlight the theoretical value of tail expansions in understanding the asymptotic behavior of CoVaR and demonstrate their practical use in developing new extreme value estimation methods. The talk also includes an empirical study that illustrates how the proposed approach can be used to assess the systemic risk in the U.S. financial industry.