Systemic Risk and Asymmetric Responses in the Financial Industry

By Germán López-Espinosa, Antonio Rubia, Laura Valderrama, Antonio Moreno

June 1, 2012

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Germán López-Espinosa, Antonio Rubia, Laura Valderrama, and Antonio Moreno. Systemic Risk and Asymmetric Responses in the Financial Industry, (USA: International Monetary Fund, 2012) accessed December 3, 2024

Disclaimer: This Working Paper should not be reported as representing the views of the IMF.The views expressed in this Working Paper are those of the author(s) and do not necessarily represent those of the IMF or IMF policy. Working Papers describe research in progress by the author(s) and are published to elicit comments and to further debate

Summary

To date, an operational measure of systemic risk capturing non-linear tail comovement between system-wide and individual bank returns has not yet been developed. This paper proposes an extension of the so-called CoVaR measure that captures the asymmetric response of the banking system to positive and negative shocks to the market-valued balance sheets of individual banks. For the median of our sample of U.S. banks, the relative impact on the system of a fall in individual market value is sevenfold that of an increase. Moreover, the downward bias in systemic risk from ignoring this asymmetric pattern increases with bank size. The conditional tail comovement between the banking system and a top decile bank which is losing market value is 5.4 larger than the unconditional tail comovement versus only 2.2 for banks in the bottom decile. The asymmetric model also produces much better estimates and fitting, and thus improves the capacity to monitor systemic risk. Our results suggest that ignoring asymmetries in tail interdependence may lead to a severe underestimation of systemic risk in a downward market.

Subject: Banking, Commercial banks, Econometric analysis, Financial institutions, Financial sector policy and analysis, Financial statements, Public financial management (PFM), Systemic risk, Treasury bills and bonds, Vector autoregression

Keywords: Banking system, Commercial banks, CoVaR approach, CoVaR estimate, CoVaR framework, CoVaR function, CoVaR measure, CoVaR model, CoVaR prediction, CoVaR process, Default premium, Descriptive statistics, Downside risk, Financial statements, Global, Risk contribution, Systemic risk, Tail-risk dependence, Time series, Treasury bills and bonds, Value at Risk, Vector autoregression, WP

Publication Details

Pages:

38
Volume:

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DOI:

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Issue:

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Series:

Working Paper No. 2012/152
Stock No:

WPIEA2012152
ISBN:

9781475504347
ISSN:

1018-5941

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