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How useful is the marginal expected shortfall for the measurement of systemic exposure? A practical assessment

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  • Idier, Julien
  • Lamé, Gildas
  • Mésonnier, Jean-Stéphane

Abstract

We explore the practical relevance from a supervisor's perspective of a popular market-based indicator of the exposure of a financial institution to systemic risk, the marginal expected shortfall (MES). The MES of an institution can be defined as its expected equity loss when the market itself is in its left tail. We estimate the dynamic MES recently proposed by Brownlees and Engle (2011) for a panel of 65 large US banks over the last decade and a half. Running panel regressions of the MES on bank characteristics, we first find that the MES can be roughly rationalized in terms of standard balance sheet indicators of bank financial soundness and systemic importance. We then ask whether the cross section of the MES can help to identify ex ante, i.e. before a crisis unfolds, which institutions are the more likely to suffer the most severe losses ex post, i.e. once it has unfolded. Unfortunately, using the recent crisis as a natural experiment, we find that standard balance-sheet metrics like the tier one solvency ratio are better able than the MES to predict equity losses conditionally to a true crisis. JEL Classification: C5, E44, G2

Suggested Citation

  • Idier, Julien & Lamé, Gildas & Mésonnier, Jean-Stéphane, 2013. "How useful is the marginal expected shortfall for the measurement of systemic exposure? A practical assessment," Working Paper Series 1546, European Central Bank.
  • Handle: RePEc:ecb:ecbwps:20131546
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    Cited by:

    1. Michal Skorepa & Jakub Seidler, 2015. "Capital buffers based on banks’ domestic systemic importance: selected issues," Journal of Financial Economic Policy, Emerald Group Publishing, vol. 7(3), pages 207-220, August.
    2. Paola Cerchiello & Paolo Giudici, 2014. "Financial big data analysis for the estimation of systemic risks," DEM Working Papers Series 086, University of Pavia, Department of Economics and Management.
    3. Jon Danielsson & Kevin R. James & Marcela Valenzuela & Ilknur Zer, 2016. "Can We Prove a Bank Guilty of Creating Systemic Risk? A Minority Report," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 48(4), pages 795-812, June.
    4. Pankoke, David, 2014. "Sophisticated vs. Simple Systemic Risk Measures," Working Papers on Finance 1422, University of St. Gallen, School of Finance.
    5. Leroy, Aurélien & Lucotte, Yannick, 2017. "Is there a competition-stability trade-off in European banking?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 46(C), pages 199-215.
    6. Olivier de Bandt & Jean-Cyprien Héam & Claire Labonne & Santiago Tavolaro, 2015. "La mesure du risque systémique après la crise financière," Revue économique, Presses de Sciences-Po, vol. 66(3), pages 481-500.
    7. Paola Cerchiello & Paolo Giudici, 2014. "Conditional graphical models for systemic risk measurement," DEM Working Papers Series 087, University of Pavia, Department of Economics and Management.
    8. S. Tavolaro & F. Visnovsky, 2014. "What is the information content of the SRISK measure as a supervisory tool?," Débats économiques et financiers 10, Banque de France.
    9. O. de Bandt & J.-C. Héam & C. Labonne & S. Tavolaro, 2013. "Measuring Systemic Risk in a Post-Crisis World," Débats économiques et financiers 6, Banque de France.
    10. Martin Eling & David Antonius Pankoke, 2016. "Systemic Risk in the Insurance Sector: A Review and Directions for Future Research," Risk Management and Insurance Review, American Risk and Insurance Association, vol. 19(2), pages 249-284, September.
    11. Shaw, Frances & Dunne, Peter G., 2017. "Investment Fund Risk: The Tale in the Tails," Research Technical Papers 01/RT/17, Central Bank of Ireland.
    12. Mikhail Stolbov, 2017. "Assessing systemic risk and its determinants for advanced and major emerging economies: the case of ΔCoVaR," International Economics and Economic Policy, Springer, pages 119-152.
    13. Asimit, Alexandru V. & Li, Jinzhu, 2016. "Extremes for coherent risk measures," Insurance: Mathematics and Economics, Elsevier, vol. 71(C), pages 332-341.
    14. Raffaella Calabrese & Johan A. Elkink & Paolo Giudici, 2014. "Measuring Bank Contagion in Europe Using Binary Spatial Regression Models," DEM Working Papers Series 096, University of Pavia, Department of Economics and Management.
    15. Mühlnickel, Janina & Weiß, Gregor N.F., 2015. "Consolidation and systemic risk in the international insurance industry," Journal of Financial Stability, Elsevier, pages 187-202.
    16. Eugenio Cerutti & Stijn Claessens, 2017. "The Great Cross-Border Bank Deleveraging: Supply Constraints and Intra-Group Frictions," Review of Finance, European Finance Association, pages 201-236.
    17. Natasha Agarwal et al, 2013. "A Systematic approach to identify systemically important firms," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2013-021, Indira Gandhi Institute of Development Research, Mumbai, India.
    18. Sylvain Benoit & Gilbert Colletaz & Christophe Hurlin & Christophe Pérignon, 2013. "A Theoretical and Empirical Comparison of Systemic Risk Measures," Working Papers halshs-00746272, HAL.
    19. Silva, Walmir & Kimura, Herbert & Sobreiro, Vinicius Amorim, 2017. "An analysis of the literature on systemic financial risk: A survey," Journal of Financial Stability, Elsevier, pages 91-114.

    More about this item

    Keywords

    balance sheet ratios; MES; panel; systemic risk; tail correlation;

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G2 - Financial Economics - - Financial Institutions and Services

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