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Credit Risk Stress Testing: An Exercise for Colombian Banks

Author

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  • Wilmar Cabrera

    ()

  • Javier Gutiérrez Rueda

    ()

  • Juan Carlos Mendoza

    ()

Abstract

In this paper we seek to assess the ability of banks to withstand the e?ects of an increase in credit risk as a result of changes in the macroeconomic environment. To do so we estimate a credit risk model for each loan type as a function of four macroeconomic variables commonly used in the literature. Then, we forecast the dynamics of non-performing loans (NPL) and total loans in a stressed scenario in a time span of 8 quarters. Using these results, we quantify the e?ects of the macroeconomic shock on bank’s performance indicators, such as the NPL ratio, the return on assets, and the capital adequacy ratio. The results suggest that most Colombian banks are able to withstand a large shock to economic activity. We also perform a reverse stress testing to quantify how much NPL should increase in order to bring the earnings before taxes to zero.

Suggested Citation

  • Wilmar Cabrera & Javier Gutiérrez Rueda & Juan Carlos Mendoza, 2012. "Credit Risk Stress Testing: An Exercise for Colombian Banks," Temas de Estabilidad Financiera 073, Banco de la Republica de Colombia.
  • Handle: RePEc:bdr:temest:073
    DOI: 10.32468/tef.73
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    File URL: https://doi.org/10.32468/tef.73
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    References listed on IDEAS

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    1. Glenn Hoggarth & Steffen Sorensen & Lea Zicchino, 2005. "Stress tests of UK banks using a VAR approach," Bank of England working papers 282, Bank of England.
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    3. Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501.
    4. David Edgerton & Ghazi Shukur, 1999. "Testing autocorrelation in a system perspective testing autocorrelation," Econometric Reviews, Taylor & Francis Journals, vol. 18(4), pages 343-386.
    5. Godfrey, Leslie G, 1978. "Testing for Higher Order Serial Correlation in Regression Equations When the Regressors Include Lagged Dependent Variables," Econometrica, Econometric Society, vol. 46(6), pages 1303-1310, November.
    6. Jim Wong & Ka-Fai Choi & Tom Pak-Wing Fong, 2008. "A Framework for Stress Testing Banks’ Credit Risk," Palgrave Macmillan Studies in Banking and Financial Institutions, in: Hans Genberg & Cho-Hoi Hui (ed.), The Banking Sector in Hong Kong, chapter 11, pages 240-260, Palgrave Macmillan.
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    Cited by:

    1. Santiago Gamba & Oscar Jaulín & Angélica Lizarazo & Juan Carlos Mendoza & Paola Morales & Daniel Osorio & Eduardo Yanquen, 2017. "SYSMO I: A Systemic Stress Model for the Colombian Financial System," Borradores de Economia 1028, Banco de la Republica de Colombia.

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    More about this item

    Keywords

    Credit Risk Stress Testing: An Exercise for Colombian Banks;

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation

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