IDEAS home Printed from https://ideas.repec.org/p/vua/wpaper/1998-1.html
   My bibliography  Save this paper

Testing backtesting : an evaluation of the Basle guidelines for backtesting internal risk management models of banks

Author

Listed:
  • Lucas, André

    (Vrije Universiteit Amsterdam, Faculteit der Economische Wetenschappen en Econometrie (Free University Amsterdam, Faculty of Economics Sciences, Business Administration and Economitrics)

Abstract

Internal risk management models and downside-risk measures such as Value-at-Risk (VaR) play an important role in contemporary banking practice. VaR measures the maximum loss born by a bank or other financial institution over a certain time period and given a certain level of confidence. Following the Basle guidelines for bank supervision, many supervisory institutions require banks to use such models and to report VaR measures on a regular basis. Capital requirements for the bank are then directly related to its reported VaR figure. In principle, following the Basle guidelines based on the internal models approach, banks are allowed to design their own risk management models for computing their VaR. This raises the question whether banks have any impetus to come up with correct models in the sense that the VaR predicted by the model matches the true VaR. This question is addressed in the present paper. In our model, banks assign negative utility to required capital reserves due to opportunity costs. Using a stylized representation of the Basle guidelines for backtesting internal risk models, we investigate whether banks are inclined to choose overly prudent or overly risky internal models. We check the robustness of the result by varying the planning horizon of the bank and the degree of fat-tailedness of the bank’s asset and liability portfolio. It generally turns out that banks have a strong incentive to use internal models that underestimate the true VaR of the bank’s portfolio. Monetary penalties should be set substantially higher by supervisory institutions to realize a closer match between reported and actual VaR.

Suggested Citation

  • Lucas, André, 1998. "Testing backtesting : an evaluation of the Basle guidelines for backtesting internal risk management models of banks," Serie Research Memoranda 0001, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
  • Handle: RePEc:vua:wpaper:1998-1
    as

    Download full text from publisher

    File URL: http://degree.ubvu.vu.nl/repec/vua/wpaper/pdf/19980001.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Paul H. Kupiec, 1995. "Techniques for verifying the accuracy of risk measurement models," Finance and Economics Discussion Series 95-24, Board of Governors of the Federal Reserve System (U.S.).
    2. Paul H. Kupiec & James M. O'Brien, 1997. "The pre-commitment approach: using incentives to set market risk capital requirements," Finance and Economics Discussion Series 1997-14, Board of Governors of the Federal Reserve System (U.S.).
    3. Pagan, Adrian, 1996. "The econometrics of financial markets," Journal of Empirical Finance, Elsevier, vol. 3(1), pages 15-102, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jeremy Berkowitz, 1999. "Evaluating the forecasts of risk models," Finance and Economics Discussion Series 1999-11, Board of Governors of the Federal Reserve System (U.S.).
    2. Flavio Bazzana, 2001. "I modelli interni per la valutazione del rischio di mercato secondo l'approccio del Value at Risk," Alea Tech Reports 011, Department of Computer and Management Sciences, University of Trento, Italy, revised 14 Jun 2008.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Szubzda Filip & Chlebus Marcin, 2019. "Comparison of Block Maxima and Peaks Over Threshold Value-at-Risk models for market risk in various economic conditions," Central European Economic Journal, Sciendo, vol. 6(53), pages 70-85, January.
    2. Baum, Christopher F. & Zerilli, Paola & Chen, Liyuan, 2021. "Stochastic volatility, jumps and leverage in energy and stock markets: Evidence from high frequency data," Energy Economics, Elsevier, vol. 93(C).
    3. Mohamed CHIKHI & Ali BENDOB & Ahmed Ramzi SIAGH, 2019. "Day-of-the-week and month-of-the-year effects on French Small-Cap Volatility: the role of asymmetry and long memory," Eastern Journal of European Studies, Centre for European Studies, Alexandru Ioan Cuza University, vol. 10, pages 221-248, December.
    4. Anand, Abhinav & Li, Tiantian & Kurosaki, Tetsuo & Kim, Young Shin, 2016. "Foster–Hart optimal portfolios," Journal of Banking & Finance, Elsevier, vol. 68(C), pages 117-130.
    5. Choi, Pilsun & Nam, Kiseok, 2008. "Asymmetric and leptokurtic distribution for heteroscedastic asset returns: The SU-normal distribution," Journal of Empirical Finance, Elsevier, vol. 15(1), pages 41-63, January.
    6. Lin, Chu-Hsiung & Changchien, Chang-Cheng & Kao, Tzu-Chuan & Kao, Wei-Shun, 2014. "High-order moments and extreme value approach for value-at-risk," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 421-434.
    7. Daniel Velásquez-Gaviria & Andrés Mora-Valencia & Javier Perote, 2020. "A Comparison of the Risk Quantification in Traditional and Renewable Energy Markets," Energies, MDPI, vol. 13(11), pages 1-42, June.
    8. Arupratan Daripa & Simone Varotto, 1997. "Agency Incentives and Reputational Distortions: a Comparison of the Effectiveness of Value-at-Risk and Pre-commitment in Regulating Market Risk," Bank of England working papers 69, Bank of England.
    9. Wang, Jying-Nan & Du, Jiangze & Hsu, Yuan-Teng, 2018. "Measuring long-term tail risk: Evaluating the performance of the square-root-of-time rule," Journal of Empirical Finance, Elsevier, vol. 47(C), pages 120-138.
    10. Bali, Turan G. & Mo, Hengyong & Tang, Yi, 2008. "The role of autoregressive conditional skewness and kurtosis in the estimation of conditional VaR," Journal of Banking & Finance, Elsevier, vol. 32(2), pages 269-282, February.
    11. Jackson, Patricia & Perraudin, William, 2000. "Regulatory implications of credit risk modelling," Journal of Banking & Finance, Elsevier, vol. 24(1-2), pages 1-14, January.
    12. Jezabel Couppey, 2000. "Vers un nouveau schéma de réglementation prudentielle : une contribution au débat," Revue d'Économie Financière, Programme National Persée, vol. 56(1), pages 37-56.
    13. Hotta, Luiz & Trucíos, Carlos & Ruiz Ortega, Esther, 2015. "Robust bootstrap forecast densities for GARCH models: returns, volatilities and value-at-risk," DES - Working Papers. Statistics and Econometrics. WS ws1523, Universidad Carlos III de Madrid. Departamento de Estadística.
    14. Lyu, Yongjian & Wang, Peng & Wei, Yu & Ke, Rui, 2017. "Forecasting the VaR of crude oil market: Do alternative distributions help?," Energy Economics, Elsevier, vol. 66(C), pages 523-534.
    15. Chebbi, Ali & Hedhli, Amel, 2022. "Revisiting the accuracy of standard VaR methods for risk assessment: Using the Copula–EVT multidimensional approach for stock markets in the MENA region," The Quarterly Review of Economics and Finance, Elsevier, vol. 84(C), pages 430-445.
    16. Gregory, Allan W. & Reeves, Jonathan J., 2008. "Interpreting Value at Risk (VaR) forecasts," Economic Systems, Elsevier, vol. 32(2), pages 167-176, June.
    17. Dilip Kumar, 2020. "Value-at-Risk in the Presence of Structural Breaks Using Unbiased Extreme Value Volatility Estimator," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 18(3), pages 587-610, September.
    18. Arupratan Daripa & Simone Varotto, 1998. "Value at risk and precommitment: approaches to market risk regulation," Economic Policy Review, Federal Reserve Bank of New York, vol. 4(Oct), pages 137-143.
    19. Zouheir Mighri & Raouf Jaziri, 2023. "Long-Memory, Asymmetry and Fat-Tailed GARCH Models in Value-at-Risk Estimation: Empirical Evidence from the Global Real Estate Markets," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 21(1), pages 41-97, March.
    20. Assaf, Ata, 2015. "Value-at-Risk analysis in the MENA equity markets: Fat tails and conditional asymmetries in return distributions," Journal of Multinational Financial Management, Elsevier, vol. 29(C), pages 30-45.

    More about this item

    Keywords

    risk management; Value-at-Risk; Basle guidelines for bank supervision and backtesting; capital requirements; fat-tailed distributions;
    All these keywords.

    JEL classification:

    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:vua:wpaper:1998-1. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: R. Dam (email available below). General contact details of provider: https://edirc.repec.org/data/fewvunl.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.