IDEAS home Printed from https://ideas.repec.org/p/ehl/lserod/66721.html

Can we prove a bank guilty of creating systemic risk? A minority report

Author

Listed:
  • Danielsson, Jon
  • James, Kevin R.
  • Valenzuela, Marcela
  • Zer, Ilknur

Abstract

Because increasing a bank's capital requirement to improve the stability of the financial system imposes costs upon the bank, a regulator should ideally be able to prove beyond a reasonable doubt that banks classified as systemically risky really do create systemic risk before subjecting them to this capital punishment. Evaluating the performance of two leading systemic risk models, we show that estimation error alone prevents the reliable identification of the most systemically risky banks. We conclude that it will be a considerable challenge to develop a riskometer that is sound and reliable enough to provide an adequate foundation for macroprudential policy.

Suggested Citation

  • Danielsson, Jon & James, Kevin R. & Valenzuela, Marcela & Zer, Ilknur, 2016. "Can we prove a bank guilty of creating systemic risk? A minority report," LSE Research Online Documents on Economics 66721, London School of Economics and Political Science, LSE Library.
    • Handle: RePEc:ehl:lserod:66721
    as

    Download full text from publisher

    File URL: https://researchonline.lse.ac.uk/id/eprint/66721/
    File Function: Open access version.
    Download Restriction: no
    ---><---

    Other versions of this item:

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Baumöhl, Eduard & Bouri, Elie & Hoang, Thi-Hong-Van & Shahzad, Syed Jawad Hussain & Výrost, Tomáš, 2020. "Increasing systemic risk during the Covid-19 pandemic: A cross-quantilogram analysis of the banking sector," EconStor Preprints 222580, ZBW - Leibniz Information Centre for Economics.
    2. Tente, Natalia & von Westernhagen, Natalja & Slopek, Ulf, 2017. "M-PRESS-CreditRisk: A holistic micro- and macroprudential approach to capital requirements," Discussion Papers 15/2017, Deutsche Bundesbank.
    3. Thomas F. Coleman & Alex LaPlante & Alexey Rubtsov, 2018. "Analysis of the SRISK measure and its application to the Canadian banking and insurance industries," Annals of Finance, Springer, vol. 14(4), pages 547-570, November.
    4. Danielsson, Jon & James, Kevin R. & Valenzuela, Marcela & Zer, Ilknur, 2016. "Model risk of risk models," Journal of Financial Stability, Elsevier, vol. 23(C), pages 79-91.
    5. Moratis, Georgios & Sakellaris, Plutarchos, 2021. "Measuring the systemic importance of banks," Journal of Financial Stability, Elsevier, vol. 54(C).
    6. Aleksandra Pasieczna-Dixit, 2025. "How reliable are systemic risk measures? Model risk estimates of MES and ΔCoVaR," Bank i Kredyt, Narodowy Bank Polski, vol. 56(4), pages 463-496.
    7. Mathias Mandla Manguzvane & John Weirstrass Muteba Mwamba, 2022. "South African Banks’ Cross-Border Systemic Risk Exposure: An Application of the GAS Copula Marginal Expected Shortfall," IJFS, MDPI, vol. 10(1), pages 1-19, March.
    8. Jokivuolle, Esa & Tunaru, Radu & Vioto, Davide, 2018. "Testing the systemic risk differences in banks," Bank of Finland Research Discussion Papers 13/2018, Bank of Finland.
    9. Garcia-Jorcano, Laura & Sanchis-Marco, Lidia, 2021. "Systemic-systematic risk in financial system: A dynamic ranking based on expectiles," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 330-365.
    10. Laura Garcia‐Jorcano & Lidia Sanchis‐Marco, 2025. "Measuring the Impact of Transition Risk on Financial Markets: A Joint VaR‐ES Approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 44(6), pages 1907-1945, September.
    11. Laura Garcia-Jorcano & Lidia Sanchis-Marco, 2023. "Measuring Systemic Risk Using Multivariate Quantile-Located ES Models," Journal of Financial Econometrics, Oxford University Press, vol. 21(1), pages 1-72.
    12. Kubitza, Christian & Gründl, Helmut, 2016. "Systemic risk: Time-lags and persistence," ICIR Working Paper Series 20/16, Goethe University Frankfurt, International Center for Insurance Regulation (ICIR).
    13. Michele Leonardo Bianchi & Alberto Maria Sorrentino, 2020. "Measuring CoVaR: An Empirical Comparison," Computational Economics, Springer;Society for Computational Economics, vol. 55(2), pages 511-528, February.
    14. Natalia Tente & Natalja Von Westernhagen & Ulf Slopek, 2019. "M‐PRESS‐CreditRisk: Microprudential and Macroprudential Capital Requirements for Credit Risk under Systemic Stress," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 51(7), pages 1923-1961, October.
    15. Naohisa Hirakata & Yosuke Kido & Jie Liang Thum, 2020. "Systemic risk and the Fallacy of Composition: Empirical Evidence from Japanese Regional Bank," International Journal of Central Banking, International Journal of Central Banking, vol. 16(4), pages 293-325, September.
    16. Moffo, Ahmadou Mustapha Fonton, 2024. "A machine learning approach in stress testing US bank holding companies," International Review of Financial Analysis, Elsevier, vol. 95(PC).
    17. Jokivuolle, Esa & Tunaru, Radu & Vioto, Davide, 2018. "Testing the systemic risk differences in banks," Research Discussion Papers 13/2018, Bank of Finland.
    18. Varotto, Simone & Zhao, Lei, 2018. "Systemic risk and bank size," Journal of International Money and Finance, Elsevier, vol. 82(C), pages 45-70.
    19. Chiara Pederzoli & Costanza Torricelli, 2017. "Systemic risk measures and macroprudential stress tests: an assessment over the 2014 EBA exercise," Annals of Finance, Springer, vol. 13(3), pages 237-251, August.
    20. Matteo Foglia & Eliana Angelini, 2021. "The triple (T3) dimension of systemic risk: Identifying systemically important banks," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 7-26, January.
    21. Abdelkader DERBALI & Ali LAMOUCHI, 2020. "RETRACTED ARTICLE: The triple (T3) dimension of systemic risk: identifying systemically important banks in Eurozone Abstract: Editor’s Note - This paper has been retracted from our journal due to bogus claims of authorship. The editors' decision is b," Eastern Journal of European Studies, Centre for European Studies, Alexandru Ioan Cuza University, vol. 11, pages 87-122, June.
    22. Gogas, Periklis & Papadimitriou, Theophilos & Agrapetidou, Anna, 2018. "Forecasting bank failures and stress testing: A machine learning approach," International Journal of Forecasting, Elsevier, vol. 34(3), pages 440-455.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G18 - Financial Economics - - General Financial Markets - - - Government Policy and Regulation
    • G20 - Financial Economics - - Financial Institutions and Services - - - General
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation
    • G38 - Financial Economics - - Corporate Finance and Governance - - - Government Policy and Regulation

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ehl:lserod:66721. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: LSERO Manager (email available below). General contact details of provider: https://edirc.repec.org/data/lsepsuk.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.