Abstract
Operational risk has become increasingly important topics for Chinese Commercial Banks in recent years. Considering the huge operational losses, Extreme value theory (EVT) has been recognized as a useful tool in analyzing such data. In this paper, we presented an ERMPOT (Exponential Regression Model and the Peaks-Over-Threshold) method to measure the operational risk. The ERM-POT method can lead to bias-corrected estimators and techniques for optimal threshold selections. And the experiment results show that the method is reasonable. © Springer-Verlag Berlin Heidelberg 2007.
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CITATION STYLE
Meng, F., Li, J., & Gao, L. (2007). ERM-POT method for quantifying operational risk for Chinese commercial banks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4488 LNCS, pp. 478–481). Springer Verlag. https://doi.org/10.1007/978-3-540-72586-2_68
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