A1238
Title: Safe distance to systemic risk
Authors: Sylvain Benoit - University Paris Dauphine - PSL (France) [presenting]
Renzhi Liu - Universite Paris Dauphine PSL (France)
Abstract: The aim is to propose a new systemic risk indicator to measure the distance to the extreme losses of a financial system. Constructed from daily out-of-sample value-at-risk (VaR) exceptions across 95 large U.S. financial institutions from 2000 to 2023, the indicator calculates the shortfall in market value during these exceptions. By applying extreme value theory (EVT) to the maximum weekly shortfalls using a half-year rolling window, we effectively model the tail risk of the financial system. The empirical analysis demonstrates that this indicator captures significant financial crises accurately, such as the Great Financial Crisis of 2008, the sovereign debt crisis of 2010, and the COVID-19 pandemic in 2020. Through quantile regression, it is shown that increases in the indicator significantly predict negative shocks to industrial production growth rates.
