Book contents
- Validation of Risk Management Models for Financial Institutions
- Validation of Risk Management Models for Financial Institutions
- Copyright page
- Contents
- Figures
- Tables
- Contributors
- Foreword
- Acknowledgments
- 1 Common Elements in Validation of Risk Models Used in Financial Institutions
- 2 Validating Bank Holding Companies’ Value-at-Risk Models for Market Risk
- 3 A Conditional Testing Approach for Value-at-Risk Model Performance Evaluation
- 4 Beyond Exceedance-Based Backtesting of Value-at-Risk Models: Methods for Backtesting the Entire Forecasting Distribution Using Probability Integral Transform
- 5 Evaluation of Value-at-Risk Models: An Empirical Likelihood Approach
- 6 Evaluating Banks’ Value-at-Risk Models during the COVID-19 Crisis
- 7 Performance Monitoring for Supervisory Stress-Testing Models
- 8 Counterparty Credit Risk
- 9 Validation of Retail Credit Risk Models
- 10 Issues in the Validation of Wholesale Credit Risk Models
- 11 Case Studies in Wholesale Risk Model Validation
- 12 Validation of Models Used by Banks to Estimate Their Allowance for Loan and Lease Losses
- 13 Operational Risk
- 14 Statistical Decisioning Tools for Model Risk Management
- 15 Validation of Risk Aggregation in Economic Capital Models
- 16 Model Validation of Interest Rate Risk (Banking Book) Models
- 17 Validation of Risk Management Models in Investment Management
- Index
- References
6 - Evaluating Banks’ Value-at-Risk Models during the COVID-19 Crisis
Published online by Cambridge University Press: 02 March 2023
- Validation of Risk Management Models for Financial Institutions
- Validation of Risk Management Models for Financial Institutions
- Copyright page
- Contents
- Figures
- Tables
- Contributors
- Foreword
- Acknowledgments
- 1 Common Elements in Validation of Risk Models Used in Financial Institutions
- 2 Validating Bank Holding Companies’ Value-at-Risk Models for Market Risk
- 3 A Conditional Testing Approach for Value-at-Risk Model Performance Evaluation
- 4 Beyond Exceedance-Based Backtesting of Value-at-Risk Models: Methods for Backtesting the Entire Forecasting Distribution Using Probability Integral Transform
- 5 Evaluation of Value-at-Risk Models: An Empirical Likelihood Approach
- 6 Evaluating Banks’ Value-at-Risk Models during the COVID-19 Crisis
- 7 Performance Monitoring for Supervisory Stress-Testing Models
- 8 Counterparty Credit Risk
- 9 Validation of Retail Credit Risk Models
- 10 Issues in the Validation of Wholesale Credit Risk Models
- 11 Case Studies in Wholesale Risk Model Validation
- 12 Validation of Models Used by Banks to Estimate Their Allowance for Loan and Lease Losses
- 13 Operational Risk
- 14 Statistical Decisioning Tools for Model Risk Management
- 15 Validation of Risk Aggregation in Economic Capital Models
- 16 Model Validation of Interest Rate Risk (Banking Book) Models
- 17 Validation of Risk Management Models in Investment Management
- Index
- References
Summary
This chapter examines how banks’ Value-at-Risk (VaR) models performed during the COVID-19 crisis using regulatory trading desk-level data. It first evaluates whether banks’ VaR models were incomplete by checking whether various factors predict backtesting exceptions. Backtesting exceptions from the past ten business days and the level of the VIX forecast future exceptions. Predictability from past backtesting exceptions rises during the COVID-19 crisis relative to 2019. The results do not find any single market factor that related to contemporaneous backtesting exceptions. These results hold both in the aggregate and across asset classes.
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- Information
- Validation of Risk Management Models for Financial InstitutionsTheory and Practice, pp. 104 - 123Publisher: Cambridge University PressPrint publication year: 2023