en
Working paper
Open access
English

Backtesting marginal expected shortfalland related systemic risk measures

Number of pages66
Publication date2020
Abstract

This paper proposes an original approach for backtesting systemic risk measures. This backtesting approach makes it possible to assess the systemic risk measure forecasts used to identify the financial institutions that contribute the most to the overall risk in the financial system. Our procedure is based on simple tests similar to those generally used to backtest the standard market risk measures such as value-at-risk or expected shortfall. We introduce a concept of violation associated with the marginal expected shortfall (MES), and we define unconditional coverage and independence tests for these violations. We can generalize these tests to any MES-based systemic risk measures such as SES, SRISK, or Delta-CoVaR. We study their asymptotic properties in the presence of estimation risk and investigate their finite sample performance via Monte Carlo simulations. An empirical application to a panel of U.S. financial institutions is conducted to assess the validity of MES, SRISK, and Delta-CoVaR forecasts issued from a GARCH-DCC model. Our results show that this model provides valid forecasts for MES and SRISK when considering a medium-term horizon. Finally, we propose an early warning system indicator for future systemic crises deduced from these backtests. Our indicator quantifies how much is the measurement error issued by a systemic risk forecast at a given point in time which can serve for the early detection of global market reversals

Keywords
  • Banking regulation
  • Hypothesis testing
  • Risk management
  • Systemic risk
Classification
  • JEL : C12
Citation (ISO format)
BANULESCU-RADU, Denisa et al. Backtesting marginal expected shortfalland related systemic risk measures. 2020
Main files (1)
Working paper
accessLevelPublic
Identifiers
  • PID : unige:134136
215views
672downloads

Technical informations

Creation04/07/2020 7:46:00 AM
First validation04/07/2020 7:46:00 AM
Update time03/15/2023 9:28:21 PM
Status update03/15/2023 9:28:21 PM
Last indexation05/05/2024 4:39:35 PM
All rights reserved by Archive ouverte UNIGE and the University of GenevaunigeBlack