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Modeling the distribution of credit losses with observable and latent factors

Author

Listed:
  • Gabriel Jiménez

    (Banco de España)

  • Javier Mencía

    (Banco de España)

Abstract
This paper develops a flexible and computationally efficient model to estimate the credit loss distribution of the loans in a banking system. We consider a sectorial structure, where default frequencies and the total number of loans are allowed to depend on macroeconomic conditions as well as on unobservable credit risk factors, which can capture contagion effects between sectors. In addition, we also model the distributions of the Exposure at Default and the Loss Given Default. We apply our model to the Spanish credit market, where we find that sectorial default frequencies are affected by a persistent latent factor. Finally, we also identify the potentially riskier sectors and perform stress tests.

Suggested Citation

  • Gabriel Jiménez & Javier Mencía, 2007. "Modeling the distribution of credit losses with observable and latent factors," Working Papers 0709, Banco de España.
    • Handle: RePEc:bde:wpaper:0709
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    References listed on IDEAS

    as
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    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Ferrari, Stijn & Van Roy, Patrick & Vespro, Cristina, 2021. "Sensitivity of credit risk stress test results: Modelling issues with an application to Belgium," Journal of Financial Stability, Elsevier, vol. 52(C).
    2. Carlos Perez Montes, 2015. "Estimation of Regulatory Credit Risk Models," Journal of Financial Services Research, Springer;Western Finance Association, vol. 48(2), pages 161-191, October.
    3. Lee, Yongwoong & Yang, Kisung, 2019. "Modeling diversification and spillovers of loan portfolios' losses by LHP approximation and copula," International Review of Financial Analysis, Elsevier, vol. 66(C).
    4. Sreejata Banerjee & Divya Murali, 2015. "Stress Test of Banks in India: A VAR Approach," Working Papers 2015-102, Madras School of Economics,Chennai,India.
    5. Stefan Kerbl & Michael Sigmund, 2011. "What Drives Aggregate Credit Risk?," Financial Stability Report, Oesterreichische Nationalbank (Austrian Central Bank), issue 22, pages 72-87.
    6. Lee, Yongwoong & Poon, Ser-Huang, 2014. "Forecasting and decomposition of portfolio credit risk using macroeconomic and frailty factors," Journal of Economic Dynamics and Control, Elsevier, vol. 41(C), pages 69-92.
    7. Maria Stefanova, 2012. "Recovery Risiko in der Kreditportfoliomodellierung," Springer Books, Springer, number 978-3-8349-4226-5, January.
    8. Memmel, Christoph & Roling, Christoph, 2021. "Risiken im Unternehmenskreditgeschäft inländischer Banken [Risks in domestic banks' corporate lending business]," Technical Papers 08/2021, Deutsche Bundesbank.
    9. Kusaya, Charles & O’Keefe, John P. & Ufier, Alexander B., 2023. "Bridging the gap from the current deposit insurance fund to a fund target," The Quarterly Review of Economics and Finance, Elsevier, vol. 88(C), pages 148-157.
    10. Carlos Pérez Montes, 2013. "Estimation of Regulatory Credit Risk Models," Working Papers 1305, Banco de España.
    11. Barro, Diana & Basso, Antonella, 2010. "Credit contagion in a network of firms with spatial interaction," European Journal of Operational Research, Elsevier, vol. 205(2), pages 459-468, September.
    12. Lee, Yongwoong & Rösch, Daniel & Scheule, Harald, 2016. "Accuracy of mortgage portfolio risk forecasts during financial crises," European Journal of Operational Research, Elsevier, vol. 249(2), pages 440-456.
    13. Lee, Yongwoong & Rösch, Daniel & Scheule, Harald, 2021. "Systematic credit risk in securitised mortgage portfolios," Journal of Banking & Finance, Elsevier, vol. 122(C).
    14. Philip Arestis & Maggie Mo Jia, 2019. "Credit risk and macroeconomic stress tests in China," Journal of Banking Regulation, Palgrave Macmillan, vol. 20(3), pages 211-225, September.
    15. Bermingham, Colin & Conefrey, Thomas, 2014. "The Irish macroeconomic response to an external shock with an application to stress testing," Journal of Policy Modeling, Elsevier, vol. 36(3), pages 454-470.
    16. Apergis, Emmanuel & Apergis, Iraklis & Apergis, Nicholas, 2019. "A new macro stress testing approach for financial realignment in the Eurozone," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 61(C), pages 52-80.
    17. Miroslav Misina & David Tessier, 2008. "Non-Linearities, Model Uncertainty, and Macro Stress Testing," Staff Working Papers 08-30, Bank of Canada.
    18. Pérez Montes, Carlos, 2014. "The effect on competition of banking sector consolidation following the financial crisis of 2008," Journal of Banking & Finance, Elsevier, vol. 43(C), pages 124-136.
    19. Memmel, Christoph & Roling, Christoph, 2021. "Risks in domestic banks' corporate lending business," Technical Papers 08/2021, Deutsche Bundesbank.
    20. Petr Gapko & Martin Smid, 2016. "Multi-Period Structural Model of a Mortgage Portfolio with Cointegrated Factors," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 66(6), pages 565-574, December.

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    More about this item

    Keywords

    credit risk; probability of default; loss distribution; stress test; contagion;
    All these keywords.

    JEL classification:

    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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