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Analyzing and Comparing Basel's III Sensitivity Based Approach for the interest rate risk in the trading book

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  • Mabelle Sayah

    (SAF - Laboratoire de Sciences Actuarielle et Financière - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon, Faculte des Sciences - Universite Saint Joseph - USJ - Université Saint-Joseph de Beyrouth)

Abstract

A bank's capital charge computation is a widely discussed topic with new approaches emerging continuously. Each bank is computing this figure using internal methodologies in order to reflect its capital adequacy; however, a more homogeneous model is recommended by the Basel committee to enable judging the situation of these financial institutions and comparing different banks among each other. In this paper, we compare different numerical and econometric models to the sensitivity based approach (SBA) implemented by BCBS under Basel III in its February 2015 publication in order to compute the capital charge, we study the influence of having several currencies and maturities within the portfolio and try to define the time horizon and confidence level implied by Basel s III approach through an application on bonds portfolios. By implementing several approaches, we are able to find equivalent VaRs to the one computed by the SBA on a pre-defined confidence level (97.5 %). However, the time horizon differs according to the chosen methodology and ranges from 1 month up to 1 year.

Suggested Citation

  • Mabelle Sayah, 2016. "Analyzing and Comparing Basel's III Sensitivity Based Approach for the interest rate risk in the trading book," Post-Print hal-01217928, HAL.
    • Handle: RePEc:hal:journl:hal-01217928
    Note: View the original document on HAL open archive server: https://hal.science/hal-01217928
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    References listed on IDEAS

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    1. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    2. 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.
    3. Siegel, Andrew F. & Nelson, Charles R., 1988. "Long-Term Behavior of Yield Curves," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 23(1), pages 105-110, March.
    4. Cristina Badarau-Semenescu, & Gregory Levieuge, 2010. "Assessing the Potential Strength of a Bank Capital Channel in Europe: A Principal Component Analysis," The Review of Finance and Banking, Academia de Studii Economice din Bucuresti, Romania / Facultatea de Finante, Asigurari, Banci si Burse de Valori / Catedra de Finante, vol. 2(1), pages 005-016, June.
    5. 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.
    6. 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.
    7. Gita Persand & Chris Brooks & Simon P. Burke, 2003. "Multivariate GARCH models: software choice and estimation issues," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(6), pages 725-734.
    8. Chistina Badarau & Grégory Levieuge, 2010. "Assessing the Potential Strength of a Bank Capital Channel in Europe: A Principal Component Analysis," Larefi Working Papers 201006, Larefi, Université Bordeaux 4.
    9. Bera, Anil K. & Jarque, Carlos M., 1981. "Efficient tests for normality, homoscedasticity and serial independence of regression residuals : Monte Carlo Evidence," Economics Letters, Elsevier, vol. 7(4), pages 313-318.
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    Cited by:

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    Keywords

    Sensitivity Based approach; Capital charge; GARCH; PCA; Basel III; bonds portfolio; Dynamic Nelson Siegel; ICA; interest rate risk; trading book;
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