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Cyclical default and recovery in stress testing loan losses

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  • Jokivuolle, Esa
  • Virén, Matti

Abstract

We present a macro variable-based empirical model for corporate bank loans’ credit risk. The model captures the well-known positive relationship between probability of default (PD) and loss given default (LGD; i.e., the inverse of recovery) and their counter-cyclical movement with the business cycle. In the absence of proper micro data on LGD, we use a random-sampling method to estimate the annual average LGD. We specify a two equation model for PD and LGD which is estimated with Finnish time-series data from 1989 to 2008. We also use a system of time-series models for the exogenous macro variables to derive the main macroeconomic shocks which are then used in stress testing aggregate loan losses. We show that the endogenous LGD makes a considerable difference in stress tests compared to a constant LGD assumption.

Suggested Citation

  • Jokivuolle, Esa & Virén, Matti, 2013. "Cyclical default and recovery in stress testing loan losses," Journal of Financial Stability, Elsevier, vol. 9(1), pages 139-149.
  • Handle: RePEc:eee:finsta:v:9:y:2013:i:1:p:139-149
    DOI: 10.1016/j.jfs.2011.10.001
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    References listed on IDEAS

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    1. Shleifer, Andrei & Vishny, Robert W, 1992. " Liquidation Values and Debt Capacity: A Market Equilibrium Approach," Journal of Finance, American Finance Association, vol. 47(4), pages 1343-1366, September.
    2. Gordy, Michael B., 2000. "A comparative anatomy of credit risk models," Journal of Banking & Finance, Elsevier, vol. 24(1-2), pages 119-149, January.
    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. Edward I. Altman & Brooks Brady & Andrea Resti & Andrea Sironi, 2005. "The Link between Default and Recovery Rates: Theory, Empirical Evidence, and Implications," The Journal of Business, University of Chicago Press, vol. 78(6), pages 2203-2228, November.
    5. Juan Carlos Conesa & Timothy J. Kehoe & Kim J. Ruhl, 2007. "Modeling great depressions: the depression in Finland in the 1990s," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Nov, pages 16-44.
    6. Stefano Caselli & Stefano Gatti & Francesca Querci, 2008. "The Sensitivity of the Loss Given Default Rate to Systematic Risk: New Empirical Evidence on Bank Loans," Journal of Financial Services Research, Springer;Western Finance Association, vol. 34(1), pages 1-34, August.
    7. Sorge, Marco & Virolainen, Kimmo, 2006. "A comparative analysis of macro stress-testing methodologies with application to Finland," Journal of Financial Stability, Elsevier, vol. 2(2), pages 113-151, June.
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    Citations

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    Cited by:

    1. Jokivuolle, Esa & Pesola, Jarmo & Viren, Matti, 2015. "Why is credit-to-GDP a good measure for setting countercyclical capital buffers?," Journal of Financial Stability, Elsevier, vol. 18(C), pages 117-126.
    2. Yao, Xiao & Crook, Jonathan & Andreeva, Galina, 2017. "Is it obligor or instrument that explains recovery rate: Evidence from US corporate bond," Journal of Financial Stability, Elsevier, vol. 28(C), pages 1-15.
    3. Memmel, Christoph & Gündüz, Yalin & Raupach, Peter, 2015. "The common drivers of default risk," Journal of Financial Stability, Elsevier, vol. 16(C), pages 232-247.
    4. Dobromił Serwa, 2013. "Measuring Non-Performing Loans During (and After) Credit Booms," Central European Journal of Economic Modelling and Econometrics, CEJEME, vol. 5(3), pages 163-183, September.
    5. Mora, Nada, 2015. "Creditor recovery: The macroeconomic dependence of industry equilibrium," Journal of Financial Stability, Elsevier, vol. 18(C), pages 172-186.
    6. Collins, Sean & Gallagher, Emily, 2016. "Assessing the credit risk of money market funds during the eurozone crisis," Journal of Financial Stability, Elsevier, vol. 25(C), pages 150-165.
    7. repec:eee:quaeco:v:68:y:2018:i:c:p:237-253 is not listed on IDEAS
    8. Abudy, Menachem Meni & Raviv, Alon, 2016. "How much can illiquidity affect corporate debt yield spread?," Journal of Financial Stability, Elsevier, vol. 25(C), pages 58-69.
    9. Fang, Yiwei & van Lelyveld, Iman, 2014. "Geographic diversification in banking," Journal of Financial Stability, Elsevier, vol. 15(C), pages 172-181.

    More about this item

    Keywords

    PD; LGD; Credit risk; Bank loans; Macroprudential analysis; Stress testing;

    JEL classification:

    • G01 - Financial Economics - - General - - - Financial Crises
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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