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A Framework for Stress Testing Bank's Credit Risk

Author

Listed:
  • Jim Wong

    (Research Department, Hong Kong Monetary Authority)

  • Ka-fai Choi

    (Research Department, Hong Kong Monetary Authority)

  • Tom Fong

    (Research Department, Hong Kong Monetary Authority)

Abstract
This paper develops a framework for stress testing the credit exposures of Hong Kong's retail banks to macroeconomic shocks. It involves the construction of macroeconomic credit risk models, each consisting of a multiple regression model explaining the default rate of banks, and a set of autoregressive models explaining the macroeconomic environment estimated by the method of seemingly unrelated regression. Specifically, two macroeconomic credit risk models are built. One model is specified for the overall loan portfolios of banks and, to illustrate how the same framework can be applied for stress testing loans to different economic sectors, the other model is specified for the banks' mortgage exposures only. The empirical results suggest a significant relationship between the default rates of bank loans and key macroeconomic factors including Hong Kong¡¦s real GDP, real interest rates, real property prices and Mainland China's real GDP. Macro stress testing is then performed to assess the vulnerability and risk exposures of banks' overall loan portfolios and mortgage exposures. By using the framework, a Monte Carlo method is applied to estimate the distribution of possible credit losses conditional on an artificially introduced shock. Different shocks are individually introduced into the framework for the stress tests. The magnitudes of the shocks are specified according to those occurred during the Asian financial crisis. The result shows that even for the Value-at-Risk (VaR) at the confidence level of 90%, banks would continue to make a profit in most stressed scenarios, suggesting that the current credit risk of the banking sector is moderate. However, under the extreme case for the VaR at the confidence level of 99%, banks' credit loss would range from a maximum of 3.22% to a maximum of 5.56% of the portfolios, and if a confidence level of 99.9% is taken, it could range from a maximum of 6.08% to a maximum of 8.95%. These estimated maximum losses are very similar to what the market experienced one year after the Asian financial crisis shock. However, the probability of such losses and beyond is very low.

Suggested Citation

  • Jim Wong & Ka-fai Choi & Tom Fong, 2006. "A Framework for Stress Testing Bank's Credit Risk," Working Papers 0615, Hong Kong Monetary Authority.
    • Handle: RePEc:hkg:wpaper:0615
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    File URL: http://www.info.gov.hk/hkma/eng/research/RM15-2006.pdf
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    Cited by:

    1. Cağatay Başarır, 2016. "A Macro Stress Test Model of Credit Risk for the Turkish Banking Sector," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 6(12), pages 762-774, December.
    2. Michal Kováč, 2018. "Approaches to stress testing for regulatory purposes by institutions using the IRBA method [Konstrukce stres testu pro regulatorní účely modelem VEC]," Český finanční a účetní časopis, Prague University of Economics and Business, vol. 2018(2), pages 43-59.
    3. Morone, Marco & Cornaglia, Anna, 2010. "An econometric model to quantify benchmark downturn LGD on residential mortgages," MPRA Paper 25588, University Library of Munich, Germany.
    4. Avouyi-Dovi, S. & Bardos, M. & Jardet, C. & Kendaoui, L. & Moquet , J., 2009. "Macro stress testing with a macroeconomic credit risk model: Application to the French manufacturing sector," Working papers 238, Banque de France.
    5. Rui Pascoal, 2012. "Macroeconomic Factors of Household Default. Is There Myopic Behaviour?," GEMF Working Papers 2012-20, GEMF, Faculty of Economics, University of Coimbra.
    6. 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.
    7. Hong Kong Monetary Authority, 2011. "Loan-to-value ratio as a macroprudential tool - Hong Kong SAR's experience and cross-country evidence," BIS Papers chapters, in: Bank for International Settlements (ed.), Capital flows, commodity price movements and foreign exchange intervention, volume 57, pages 163-178, Bank for International Settlements.
    8. 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.
    9. Chang Liu & Lin Tang & Dongtao Lin & Jiayi Guo, 2023. "Testing to extreme: An application of reverse stress testing engineering on mortgages of commercial banks in China," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 187-192, January.
    10. Javier Gutiérrez Rueda, 2010. "Un análisis de riesgo de crédito de las empresas del sector real y sus determinantes," Temas de Estabilidad Financiera 046, Banco de la Republica de Colombia.
    11. Vazquez, Francisco & Tabak, Benjamin M. & Souto, Marcos, 2012. "A macro stress test model of credit risk for the Brazilian banking sector," Journal of Financial Stability, Elsevier, vol. 8(2), pages 69-83.
    12. Adams, Charles, 2008. "Emerging East Asian Banking Systems Ten Years after the 1997/98 Crisis," Working Papers on Regional Economic Integration 16, Asian Development Bank.
    13. Tom Pak-wing Fong & Chun-shan Wong, 2008. "Stress Testing Banks' Credit Risk Using Mixture Vector Autoregressive Models," Working Papers 0813, Hong Kong Monetary Authority.
    14. 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.
    15. Bo Jiang & Bruce Philp & Zhongmin Wu, 2018. "Macro stress testing in the banking system of China," Journal of Banking Regulation, Palgrave Macmillan, vol. 19(4), pages 287-298, November.
    16. Abdelaziz Rouabah, 2007. "Mesure de la vulnérabilité du secteur bancaire luxembourgeois," BCL working papers 24, Central Bank of Luxembourg.
    17. Michal Kováč, 2018. "Comparison of stress testing models for regulatory purposes by institutions using the IRBA method [Porovnání stres test modelů pro regulatorní účely institucí využívajících IRBA metodu]," Český finanční a účetní časopis, Prague University of Economics and Business, vol. 2018(3), pages 41-56.

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