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Are the Basel II requirements justified in the presence of structural breaks?

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  • Par Sjolander

Abstract

The Basel Accord and the Swedish regulatory authority Finansinspektionen stipulate that banks and securities firms are obliged to estimate their Internal Risk Management Models (IRMMs) based on a minimum time series estimation period length of 1 year back in time. In this article, the Minimum Capital Risk Requirements (MCRRs) are estimated using moving windows of Swedish long and short OMX index futures positions that are bootstrapped (in blocks) by the use of Value-at-Risk Exponential Generalized Autoregressive Conditional Heteroscedasticity (VaR-(E)GARCH) models. In order to detect and adjust for structural changes in the variance, a so-called Iterative Cumulative Sums of Squares (ICSS) algorithm is applied. By the use of the earlier-mentioned approach, it is concluded that out-of-sample risk predictions are more accurate when using estimation periods shorter than 1 year, probably since relevant information are outdated fairly quickly on the markets. Therefore, the Basel Committee can discard the 1-year requirement without increased risk of financial instability.

Suggested Citation

  • Par Sjolander, 2009. "Are the Basel II requirements justified in the presence of structural breaks?," Applied Financial Economics, Taylor & Francis Journals, vol. 19(12), pages 985-998.
    • Handle: RePEc:taf:apfiec:v:19:y:2009:i:12:p:985-998
    DOI: 10.1080/09603100701704298
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    References listed on IDEAS

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    1. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    2. Farooq Malik & Bradley Ewing & James Payne, 2005. "Measuring volatility persistence in the presence of sudden changes in the variance of Canadian stock returns," Canadian Journal of Economics, Canadian Economics Association, vol. 38(3), pages 1037-1056, August.
    3. Giampiero Gallo & Barbara Pacini, 2000. "The effects of trading activity on market volatility," The European Journal of Finance, Taylor & Francis Journals, vol. 6(2), pages 163-175.
    4. repec:bla:manchs:v:70:y:2002:i:5:p:666-81 is not listed on IDEAS
    5. Philip Hans Franses & Dick van Dijk & Andre Lucas, 2004. "Short patches of outliers, ARCH and volatility modelling," Applied Financial Economics, Taylor & Francis Journals, vol. 14(4), pages 221-231.
    6. James G. MacKinnon, 2002. "Bootstrap inference in econometrics," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 35(4), pages 615-645, November.
    7. C. Brooks & A. D. Clare & G. Persand, 2002. "A Note on Estimating Market–based Minimum Capital Risk Requirements: A Multivariate GARCH Approach," Manchester School, University of Manchester, vol. 70(5), pages 666-681, September.
    8. Elliott, Graham & Rothenberg, Thomas J & Stock, James H, 1996. "Efficient Tests for an Autoregressive Unit Root," Econometrica, Econometric Society, vol. 64(4), pages 813-836, July.
    9. Engle, Robert F & Ng, Victor K, 1993. "Measuring and Testing the Impact of News on Volatility," Journal of Finance, American Finance Association, vol. 48(5), pages 1749-1778, December.
    10. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    11. Brooks, C. & Clare, A. D. & Persand, G., 2000. "A word of caution on calculating market-based minimum capital risk requirements," Journal of Banking & Finance, Elsevier, vol. 24(10), pages 1557-1574, October.
    12. Lamoureux, Christopher G & Lastrapes, William D, 1990. "Persistence in Variance, Structural Change, and the GARCH Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(2), pages 225-234, April.
    13. Hsieh, David A., 1993. "Implications of Nonlinear Dynamics for Financial Risk Management," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 28(1), pages 41-64, March.
    14. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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    Cited by:

    1. Liu, Xiaochun, 2017. "An integrated macro-financial risk-based approach to the stressed capital requirement," Review of Financial Economics, Elsevier, vol. 34(C), pages 86-98.

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