Abstract

Correlations play an important role in the risk management of banks. Changes of correlation are an important element of an adverse (stress) scenario in the BCBS framework. The purpose of this paper is to show how correlation is plagued by a number of issues that include volatility, directionality and autocorrelation. To that end, we analyze to which degree directionality and autocorrelation of correlation remove diversification benefits when they are most needed, i.e. in a crisis, and how autocorrelation amplifies correlation and makes it more persistent, creating the illusion of stable, reliable correlation levels. Furthermore, we exemplify changing correlations during the COVID-19 pandemic looking at a number of different markets. Our results suggest that prudent bank risk management should be cautious when calibrating its risk models to historical correlation levels. Market price-based stress tests should include various levels of assumed correlation as inputs to the statistical models used to assess a bank’s viability. We propose how banking supervisors and macro prudential authorities should challenge banks’ correlation assumptions and assess the rigor of applying them.

Highlights

  • Correlations play an important role in the risk management of banks

  • Our results suggest that prudent bank risk management should be cautious when calibrating its risk models to historical correlation levels

  • To address the problems when using constant correlation measures in risk management we analyze the effects of changes in correlation, identify reasons for autocorrelation of correlation, discuss changes in correlation caused by the COVID-19 pandemic and suggest how supervisors can challenge banks’ correlation assumptions and assess the rigor of applying them

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Summary

Introduction

Correlations play an important role in the risk management of banks. On a portfolio level, diversification benefits are typically measured by the degree of correlation between individual securities; on a balance sheet level, correlation between various balance sheet items measures offsetting price effects to interest. One of the most widely used frameworks of risk management in the financial markets is Value-at-Risk (Var). Increasing correlation parameters in a VaR model will lead to a higher risk assessment for the overall portfolio. Correlation, a measurement of the dependence or independence of financial time series and typically estimated quantitatively as the linear correlation coefficient of return, has always known to be plagued by a number of shortcomings. To address the problems when using constant correlation measures in risk management we analyze the effects of changes in correlation, identify reasons for autocorrelation of correlation, discuss changes in correlation caused by the COVID-19 pandemic and suggest how supervisors can challenge banks’ correlation assumptions and assess the rigor of applying them.

Supervisory Framework
Correlation Estimates and Correlation Volatility
Directionality of Correlation
Autocorrelation of Correlation
Market Makers
Hedgers
Arbitrageurs
Combined Effect
Correlation during the COVID-19 Pandemic
Implications for Supervisors
Reverse Stress Testing
Recovery Planning
Findings
Conclusion
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