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Stress testing interest rate risk exposure

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  • Abdymomunov, Azamat
  • Gerlach, Jeffrey

Abstract

In the current low interest rate environment, the possibility of a sudden increase in rates is a potentially serious threat to financial stability. As a result, analyzing interest rate risk (IRR) is critical for financial institutions and supervisory agencies. We propose a new method for generating yield-curve scenarios for stress testing banks’ exposure to IRR based on the Nelson-Siegel (1987) yield-curve model. We show that our method produces yield-curve scenarios with a wider variety of slopes and shapes than scenarios generated by the historical and hypothetical methods typically used in the banking industry and proposed in the literature. We stress test the economic value of equity of a bank balance sheet based on Call Report data from a large U.S. bank. We show that our method provides more information about the bank’s exposure to IRR using fewer yield-curve scenarios than the alternative historical and hypothetical methods.

Suggested Citation

  • Abdymomunov, Azamat & Gerlach, Jeffrey, 2014. "Stress testing interest rate risk exposure," Journal of Banking & Finance, Elsevier, vol. 49(C), pages 287-301.
  • Handle: RePEc:eee:jbfina:v:49:y:2014:i:c:p:287-301
    DOI: 10.1016/j.jbankfin.2014.08.013
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    as
    1. Qiang Dai & Kenneth J. Singleton, 2000. "Specification Analysis of Affine Term Structure Models," Journal of Finance, American Finance Association, vol. 55(5), pages 1943-1978, October.
    2. Christensen, Jens H.E. & Diebold, Francis X. & Rudebusch, Glenn D., 2011. "The affine arbitrage-free class of Nelson-Siegel term structure models," Journal of Econometrics, Elsevier, vol. 164(1), pages 4-20, September.
    3. Andrew Ang & Jean Boivin & Sen Dong & Rudy Loo-Kung, 2011. "Monetary Policy Shifts and the Term Structure," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 78(2), pages 429-457.
    4. Ang, Andrew & Piazzesi, Monika, 2003. "A no-arbitrage vector autoregression of term structure dynamics with macroeconomic and latent variables," Journal of Monetary Economics, Elsevier, vol. 50(4), pages 745-787, May.
    5. AfDB AfDB, . "Annual Report 2012 (Arabic Version)," Annual Report, African Development Bank, number 462.
    6. Andrew Ang & Sen Dong & Monika Piazzesi, 2005. "No-arbitrage Taylor rules," Proceedings, Federal Reserve Bank of San Francisco.
    7. Chib, Siddhartha & Ergashev, Bakhodir, 2009. "Analysis of Multifactor Affine Yield Curve Models," Journal of the American Statistical Association, American Statistical Association, vol. 104(488), pages 1324-1337.
    8. Diebold, Francis X. & Li, Canlin, 2006. "Forecasting the term structure of government bond yields," Journal of Econometrics, Elsevier, vol. 130(2), pages 337-364, February.
    9. Ang, Andrew & Bekaert, Geert & Wei, Min, 2007. "Do macro variables, asset markets, or surveys forecast inflation better?," Journal of Monetary Economics, Elsevier, vol. 54(4), pages 1163-1212, May.
    10. Qiang Dai & Kenneth J. Singleton & Wei Yang, 2007. "Regime Shifts in a Dynamic Term Structure Model of U.S. Treasury Bond Yields," The Review of Financial Studies, Society for Financial Studies, vol. 20(5), pages 1669-1706, 2007 12.
    11. Winklevoss, Howard E, 1982. "Plasm: Pension Liability and Asset Simulation Model," Journal of Finance, American Finance Association, vol. 37(2), pages 585-594, May.
    12. Christensen, Jens H.E. & Lopez, Jose A. & Rudebusch, Glenn D., 2015. "A probability-based stress test of Federal Reserve assets and income," Journal of Monetary Economics, Elsevier, vol. 73(C), pages 26-43.
    13. Almeida, Caio & Vicente, José, 2009. "Are interest rate options important for the assessment of interest rate risk?," Journal of Banking & Finance, Elsevier, vol. 33(8), pages 1376-1387, August.
    14. Ang, Andrew & Piazzesi, Monika & Wei, Min, 2006. "What does the yield curve tell us about GDP growth?," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 359-403.
    15. Gülpinar, Nalan & Pachamanova, Dessislava, 2013. "A robust optimization approach to asset-liability management under time-varying investment opportunities," Journal of Banking & Finance, Elsevier, vol. 37(6), pages 2031-2041.
    16. Arthur Charpentier & Christophe Villa, 2010. "Generating Yield Curve Stress-Scenarios," Working Papers hal-00550582, HAL.
    17. AfDB AfDB, . "Annual Report 2012," Annual Report, African Development Bank, number 461.
    18. Hull, John & White, Alan, 1993. "One-Factor Interest-Rate Models and the Valuation of Interest-Rate Derivative Securities," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 28(2), pages 235-254, June.
    19. Gulpinar, Nalan & Rustem, Berc & Settergren, Reuben, 2004. "Simulation and optimization approaches to scenario tree generation," Journal of Economic Dynamics and Control, Elsevier, vol. 28(7), pages 1291-1315, April.
    20. Gurkaynak, Refet S. & Sack, Brian & Wright, Jonathan H., 2007. "The U.S. Treasury yield curve: 1961 to the present," Journal of Monetary Economics, Elsevier, vol. 54(8), pages 2291-2304, November.
    21. Drehmann, Mathias & Sorensen, Steffen & Stringa, Marco, 2010. "The integrated impact of credit and interest rate risk on banks: A dynamic framework and stress testing application," Journal of Banking & Finance, Elsevier, vol. 34(4), pages 713-729, April.
    22. Nelson, Charles R & Siegel, Andrew F, 1987. "Parsimonious Modeling of Yield Curves," The Journal of Business, University of Chicago Press, vol. 60(4), pages 473-489, October.
    23. Diebold, Francis X. & Rudebusch, Glenn D. & Borag[caron]an Aruoba, S., 2006. "The macroeconomy and the yield curve: a dynamic latent factor approach," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 309-338.
    24. AfDB AfDB, . "Annual Report 2012 (Portuguese Version)," Annual Report, African Development Bank, number 463.
    25. Caio Ibsen Rodrigues De Almeida, 2004. "Time-Varying Risk Premia In Emerging Markets: Explanation By A Multi-Factor Affine Term Structure Model," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 7(07), pages 919-947.
    26. Darrell Duffie & Rui Kan, 1996. "A Yield‐Factor Model Of Interest Rates," Mathematical Finance, Wiley Blackwell, vol. 6(4), pages 379-406, October.
    27. AfDB AfDB, . "Zambia Country Office Annual Report 2012," Annual Report, African Development Bank, number 975.
    28. WorldFish, 2013. "Annual report 2012/13," Monographs, The WorldFish Center, number 40306, April.
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    Cited by:

    1. Christensen, Jens H.E. & Lopez, Jose A. & Rudebusch, Glenn D., 2015. "A probability-based stress test of Federal Reserve assets and income," Journal of Monetary Economics, Elsevier, vol. 73(C), pages 26-43.
    2. Claußen, Catharina & Platte, Daniel, 2023. "Evaluating the validity of regulatory interest rate risk measures – a simulation approach," Journal of Banking & Finance, Elsevier, vol. 154(C).
    3. Yevgeny Mugerman & Joseph Tzur & Arie Jacobi, 2018. "Mortgage Loans and Bank Risk Taking: Finding the Risk “Sweet Spot”," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 8(04), pages 1-30, December.
    4. Schmidhammer, Christoph & Hille, Vanessa & Wiedemann, Arnd, 2020. "Performance of maturity transformation strategies," Discussion Papers 58/2020, Deutsche Bundesbank.
    5. Johan Hagenbjörk & Jörgen Blomvall, 2019. "Simulation and evaluation of the distribution of interest rate risk," Computational Management Science, Springer, vol. 16(1), pages 297-327, February.
    6. Salvador Climent-Serrano, 2017. "Econometric Model to Estimate Defaults on Payment in the Spanish Financial Sector in Oliver Wyman¡¯s Stress Tests," Applied Finance and Accounting, Redfame publishing, vol. 3(1), pages 24-35, February.
    7. Serhat Yuksel & Sinemis Zengin, 2016. "Identifying the Determinants of Interest Rate Risk of the Banks," International Journal of Research in Business and Social Science (2147-4478), Center for the Strategic Studies in Business and Finance, vol. 5(6), pages 12-28, October.
    8. Michele Leonardo Bianchi, 2018. "Are multi-factor Gaussian term structure models still useful? An empirical analysis on Italian BTPs," Papers 1805.09996, arXiv.org.
    9. Pliszka, Kamil, 2021. "System-wide and banks' internal stress tests: Regulatory requirements and literature review," Discussion Papers 19/2021, Deutsche Bundesbank.
    10. Cerrone, Rosaria & Cocozza, Rosa & Curcio, Domenico & Gianfrancesco, Igor, 2017. "Does prudential regulation contribute to effective measurement and management of interest rate risk? Evidence from Italian banks," Journal of Financial Stability, Elsevier, vol. 30(C), pages 126-138.

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    More about this item

    Keywords

    Bank; Interest rate risk; Stress testing; Scenario generation; Nelson-Siegel model;
    All these keywords.

    JEL classification:

    • E47 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Forecasting and Simulation: Models and Applications
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation

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