Advances in Risk Management

(Michael S) #1
20 DETERMINATION OF THE CAPITAL CHARGE FOR OPERATIONAL RISK


  1. Consistentmeans that for largen, the estimates converge to the true value of the
    parameters,Unbiasedmeans that for all sample sizes the parameter of interest is
    calculated correctly,Efficientmeans that the ML estimate is the estimate with the
    smallest variance whileSufficientindicates that is uses all the information in the
    observations.

  2. Note that, for the Poisson distribution,χ^2 converges exactly to the chi-square dis-
    tributions withk−1 degrees of freedom. See for instance section 6.6.2 of Law and
    Kelton (2000) for a discussion on this test.

  3. SeeAppendixAofKlugmanetal.(1998)forawiderrangeofcontinuousdistributions.

  4. See BCBS, 2004, § 673.

  5. This approach is not Basel II compliant as it assumes independence between the
    various loss event types of a given business line. While this should be carefully kept
    in mind, it does not have an impact of the results of the present study and allows us
    increasing the size of samples under consideration.

  6. Themeansquareerrorsassociatedwiththeoptimumthresholdsare0.0588and0.0402
    for BL1 and BL2, respectively.

  7. In the MLE estimation, the location parameter is fixed to the optimized value
    obtained with the algorithm.

  8. We assume that the bank under consideration in this study accounts for expected
    losses in its tariff policy. Regulatory capital charge is the difference between unex-
    pected loss (the 0.999th quantile of the aggregate loss distribution) and expected loss
    (the mean of the aggregate loss distribution).

  9. We choose the MSE criterion because it explicitly accounts for both the bias and
    inefficiency effects (see Theil, 1971).


REFERENCES

Alexander, C. (2003)Operational Risk: Regulation, Analysis and Management(London: FT
Prentice-Hall).
Balkema, A.A. and de Haan, L. (1974) “Residual Life Time at Great Age”,Annals of
Probability, 2: 792–804.
Basel Committee on Banking Supervision (2004)International Convergence of Capital Mea-
surement and Capital Standards – A Revised Framework. Basel Committee Publications
No. 107, The Bank for International Settlements, Basel, Switzerland.
Chapelle, A., Crama, Y., Hübner, G. and Peters, J.P. (2005) “Measuring and Managing
Operational Risk in the Financial Sector: An Integrated Framework”, Working Paper,
University of Liège, Belgium.
Cramer, H. (1928) “On the Composition of Elementary Errors”,Skandinavisk Aktuarietid-
skrift, 11: 141–80.
Cruz, M.G. (2002)Modeling, Measuring and Hedging Operational Risk(New York: Wiley &
Sons).
Dupuis, D.J. (1999) “Exceedances over High Thresholds: AGuide to Threshold Selection”,
Extremes1: 251–61.
Embrechts, P., Furrer, H. and Kaufmann, R. (2003) “Quantifying Regulatory Capital for
Operational Risk”, Working Paper, RiskLab, ETH Zürich.
Embrechts, P., Klüppelberg, C. and Mikosch, T. (1997)Modelling Extremal Events for
Insurance and Finance(Berlin: Springer-Verlag).
de Fontnouvelle, P., Jordan, J. and Rosengren, E. (2003) “Using Loss Data to Quantify
Operational Risk”, Working Paper, Federal Reserve Bank of Boston.

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