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Testing for the Systemically Important Financial Institutions: a Conditional Approach

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  • Sessi Tokpavi

Abstract

We introduce in this paper a testing approach that allows checking whether two financial institutions are systemically equivalent, with systemic risk measured by CoVaR (Adrian and Brunnermeier, 2011). The test compares the difference in CoVaR forecasts for two financial institutions via a suitable loss function that has an economic content. Our testing approach differs from those in the literature in the sense that it is conditional, and helps evaluating in a forward-looking manner, the extent to which statistically significant differences in CoVaR forecasts can be attributed to lag values of market state variables. Moreover, the test can be used to identify systemically important financial institutions (SIFIs). Extensive Monte Carlo simulations show that the test has desirable small sample properties. With an application on a sample including 70 large U.S. financial institutions, our conditional test using market state variables such as VIX and various yield spreads, reveals more (resp. less) heterogeneity in the systemic profiles of these institutions compared to its unconditional version, in crisis (resp. non-crisis) period. It also emerges that the systemic ranking provided by our testing approach is a good forecast of a financial institution's sensitivity to a crisis. This is in contrast to the ranking obtained directly using CoVaR forecasts which has less predictive power because of estimation uncertainty.

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File URL: http://economix.fr/pdf/dt/2013/WP_EcoX_2013-27.pdf
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Bibliographic Info

Paper provided by University of Paris West - Nanterre la Défense, EconomiX in its series EconomiX Working Papers with number 2013-27.

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Length: 34 pages
Date of creation: 2013
Date of revision:
Handle: RePEc:drm:wpaper:2013-27

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Related research

Keywords: Systemic Risk; SIFIs; CoVaR; Estimation Uncertainty; Conditional Predictive Ability Test.;

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  1. Acharya, Viral V & Pedersen, Lasse H & Philippon, Thomas & Richardson, Matthew P, 2012. "Measuring Systemic Risk," CEPR Discussion Papers 8824, C.E.P.R. Discussion Papers.
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  4. Huang, Xin & Zhou, Hao & Zhu, Haibin, 2009. "A framework for assessing the systemic risk of major financial institutions," Journal of Banking & Finance, Elsevier, vol. 33(11), pages 2036-2049, November.
  5. Matteo Barigozzi & Christian Brownlees, 2013. "Nets: Network Estimation for Time Series," Working Papers 723, Barcelona Graduate School of Economics.
  6. Viral V. Acharya, 2010. "Measuring systemic risk," Proceedings 1140, Federal Reserve Bank of Chicago.
  7. Christian Capuano, 2008. "The option-iPoD. The Probability of Default Implied by Option Prices based on Entropy," IMF Working Papers 08/194, International Monetary Fund.
  8. Getmansky, Mila & Lo, Andrew W. & Makarov, Igor, 2004. "An econometric model of serial correlation and illiquidity in hedge fund returns," Journal of Financial Economics, Elsevier, vol. 74(3), pages 529-609, December.
  9. Andreas A. Jobst & Dale F. Gray, 2013. "Systemic Contingent Claims Analysis – Estimating Market-Implied Systemic Risk," IMF Working Papers 13/54, International Monetary Fund.
  10. repec:fip:fedhpr:y:2010:i:may:p:65-71 is not listed on IDEAS
  11. Arturo Estrella & Mary R. Trubin, 2006. "The yield curve as a leading indicator: some practical issues," Current Issues in Economics and Finance, Federal Reserve Bank of New York, vol. 12(Jul).
  12. Viral Acharya & Robert Engle & Matthew Richardson, 2012. "Capital Shortfall: A New Approach to Ranking and Regulating Systemic Risks," American Economic Review, American Economic Association, vol. 102(3), pages 59-64, May.
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