IDEAS home Printed from https://ideas.repec.org/p/bcl/bclwop/bclwp182.html
   My bibliography  Save this paper

Decomposing systemic risk measures by bank business model in Luxembourg

Author

Listed:
  • Xisong Jin

Abstract

This paper introduces a forward-looking bank-level stress testing framework for a large-scale system to assess three forms of banking system vulnerability– bank capital fragility, bank capital adequacy and bank solvency. Results for Luxembourg are provided with a decomposition by bank business model and domicile type. The paper goes on to assess how these systemic risk indicators are linked to macroeconomic variables, and investigates their predictive power for Luxembourg’s nominal GDP growth one year ahead. Several important findings are documented over 2003Q2 to 2023Q3. First, the systemic risk indicators responded to the main stock market crashes in a timely manner. However, contributions from different bank business models and domicile types varied over time. Second, association with key macroeconomic variables (interest rates, liquidity flow, euro area consumer confidence and business climate) depended on the different characteristics of systemic risk across bank business models. Third, the systemic risk indicators contributed to explaining nominal GDP growth one year ahead. However, the systemic risk component associated with search-for-yield behavior and fee & commission generating activities could also explain nominal GDP growth, suggesting that if banks became more dependent on these income sources, they could create financial stability issues in the long run. Overall, the framework provides a useful monitoring toolkit that tracks changes in forward-looking systemic risk and risk spillovers in the Luxembourg banking sector.

Suggested Citation

  • Xisong Jin, 2024. "Decomposing systemic risk measures by bank business model in Luxembourg," BCL working papers 182, Central Bank of Luxembourg.
  • Handle: RePEc:bcl:bclwop:bclwp182
    as

    Download full text from publisher

    File URL: https://www.bcl.lu/en/publications/Working-papers/182/BCLWP182.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Matthew Baron & Emil Verner & Wei Xiong, 2021. "Banking Crises Without Panics," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 136(1), pages 51-113.
    2. Mr. Marcos R Souto & Mr. Rodolphe Blavy, 2009. "Estimating Default Frequencies and Macrofinancial Linkages in the Mexican Banking Sector," IMF Working Papers 2009/109, International Monetary Fund.
    3. Abdelaziz Rouabah & John Theal, 2010. "Stress testing: The impact of shocks on the capital needs of the Luxembourg banking sector," BCL working papers 47, Central Bank of Luxembourg.
    4. Dimitrios Bisias & Mark Flood & Andrew W. Lo & Stavros Valavanis, 2012. "A Survey of Systemic Risk Analytics," Annual Review of Financial Economics, Annual Reviews, vol. 4(1), pages 255-296, October.
    5. McNeil, Alexander J. & Frey, Rudiger, 2000. "Estimation of tail-related risk measures for heteroscedastic financial time series: an extreme value approach," Journal of Empirical Finance, Elsevier, vol. 7(3-4), pages 271-300, November.
    6. Mr. C. A. E. Goodhart & Miguel A. Segoviano, 2009. "Banking Stability Measures," IMF Working Papers 2009/004, International Monetary Fund.
    7. Paolo Guarda & Abdelaziz Rouabah & John Theal, 2011. "An MVAR Framework to Capture Extreme Events in Macroprudential Stress Tests," BCL working papers 63, Central Bank of Luxembourg.
    8. Bollerslev, Tim, 1990. "Modelling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH Model," The Review of Economics and Statistics, MIT Press, vol. 72(3), pages 498-505, August.
    9. Cavit Pakel & Neil Shephard & Kevin Sheppard & Robert F. Engle, 2021. "Fitting Vast Dimensional Time-Varying Covariance Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(3), pages 652-668, July.
    10. Lehar, Alfred, 2005. "Measuring systemic risk: A risk management approach," Journal of Banking & Finance, Elsevier, vol. 29(10), pages 2577-2603, October.
    11. Geske, Robert, 1977. "The Valuation of Corporate Liabilities as Compound Options," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 12(4), pages 541-552, November.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Xisong Jin, 2018. "How much does book value data tell us about systemic risk and its interactions with the macroeconomy? A Luxembourg empirical evaluation," BCL working papers 118, Central Bank of Luxembourg.
    2. Jin, Xisong & Nadal De Simone, Francisco de A., 2014. "Banking systemic vulnerabilities: A tail-risk dynamic CIMDO approach," Journal of Financial Stability, Elsevier, vol. 14(C), pages 81-101.
    3. Reboredo, Juan C. & Ugolini, Andrea, 2015. "A vine-copula conditional value-at-risk approach to systemic sovereign debt risk for the financial sector," The North American Journal of Economics and Finance, Elsevier, vol. 32(C), pages 98-123.
    4. López-Espinosa, Germán & Moreno, Antonio & Rubia, Antonio & Valderrama, Laura, 2012. "Short-term wholesale funding and systemic risk: A global CoVaR approach," Journal of Banking & Finance, Elsevier, vol. 36(12), pages 3150-3162.
    5. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2013. "Financial Risk Measurement for Financial Risk Management," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 1127-1220, Elsevier.
    6. Viral V. Acharya & Lasse H. Pedersen & Thomas Philippon & Matthew Richardson, 2017. "Measuring Systemic Risk," The Review of Financial Studies, Society for Financial Studies, vol. 30(1), pages 2-47.
    7. Brunnermeier, Markus K. & Oehmke, Martin, 2013. "Bubbles, Financial Crises, and Systemic Risk," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 1221-1288, Elsevier.
    8. Ellis, Scott & Sharma, Satish & Brzeszczyński, Janusz, 2022. "Systemic risk measures and regulatory challenges," Journal of Financial Stability, Elsevier, vol. 61(C).
    9. Hossein Dastkhan, 2021. "Network‐based early warning system to predict financial crisis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 594-616, January.
    10. Cincinelli, Peter & Pellini, Elisabetta & Urga, Giovanni, 2021. "Leverage and systemic risk pro-cyclicality in the Chinese financial system," International Review of Financial Analysis, Elsevier, vol. 78(C).
    11. Jin Xisong & Lehnert Thorsten, 2018. "Large portfolio risk management and optimal portfolio allocation with dynamic elliptical copulas," Dependence Modeling, De Gruyter, vol. 6(1), pages 19-46, February.
    12. Mustafa Hakan Eratalay & Ariana Paola Cortés Ángel, 2022. "The Impact of ESG Ratings on the Systemic Risk of European Blue-Chip Firms," JRFM, MDPI, vol. 15(4), pages 1-41, March.
    13. Chowdhury, Biplob & Dungey, Mardi & Kangogo, Moses & Sayeed, Mohammad Abu & Volkov, Vladimir, 2019. "The changing network of financial market linkages: The Asian experience," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 71-92.
    14. Kwangmin Jung & Donggyu Kim & Seunghyeon Yu, 2022. "Next generation models for portfolio risk management: An approach using financial big data," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 89(3), pages 765-787, September.
    15. Ghufran Ahmad & Muhammad Suhail Rizwan & Dawood Ashraf, 2021. "Systemic risk and macroeconomic forecasting: A globally applicable copula‐based approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1420-1443, December.
    16. Jin, Xisong & Nadal De Simone, Francisco, 2014. "A framework for tracking changes in the intensity of investment funds' systemic risk," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 343-368.
    17. Drakos, Anastassios A. & Kouretas, Georgios P., 2015. "Bank ownership, financial segments and the measurement of systemic risk: An application of CoVaR," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 127-140.
    18. Berens, Tobias & Weiß, Gregor N.F. & Wied, Dominik, 2015. "Testing for structural breaks in correlations: Does it improve Value-at-Risk forecasting?," Journal of Empirical Finance, Elsevier, vol. 32(C), pages 135-152.
    19. Caporin, Massimiliano & McAleer, Michael, 2014. "Robust ranking of multivariate GARCH models by problem dimension," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 172-185.
    20. Francq, Christian & Zakoian, Jean-Michel, 2014. "Estimating multivariate GARCH and stochastic correlation models equation by equation," MPRA Paper 54250, University Library of Munich, Germany.

    More about this item

    Keywords

    Financial stability; systemic risk; macro-prudential policy; dynamic dependence; banking business model; financial stress index; coronavirus COVID-19; macro-financial linkages.;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • E5 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit
    • F3 - International Economics - - International Finance
    • G1 - Financial Economics - - General Financial Markets

    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:bcl:bclwop:bclwp182. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/bclgvlu.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.