Risk Management

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By Greg N. Gregoriou (eds.)

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1999) “Exceedances over High Thresholds: A Guide to Threshold Selection”, Extremes 1: 251–61. , Furrer, H. and Kaufmann, R. (2003) “Quantifying Regulatory Capital for Operational Risk”, Working Paper, RiskLab, ETH Zürich. , Klüppelberg, C. and Mikosch, T. (1997) Modelling Extremal Events for Insurance and Finance (Berlin: Springer-Verlag). , Jordan, J. and Rosengren, E. (2003) “Using Loss Data to Quantify Operational Risk”, Working Paper, Federal Reserve Bank of Boston. , Rosengren, E. and Jordan, J.

11. 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). 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 Measurement and Capital Standards – A Revised Framework. Basel Committee Publications No.

It must be maximized in order to estimate θ. Usually, the quality of distribution fitting is assessed through goodnessof-fit tests. All these tests are based on a comparison between the observed cumulative distribution function and the hypothetical one. Consequently, they should be adjusted to account for the collection threshold as well. 68) distribution. 2 reports three cases: In Case 1, the whole series is considered (for example, there is no collection threshold) and the parameters are estimated by the Maximum Likelihood technique.

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