The application of generalized pareto distribution and copula functions in the issue of operational risk

• Authors: Krzysztof Basiaga , Tomasz Szkutnik
• Languages of publication: EN

Abstracts

EN

The article concerns the issue of modelling of operational risk in a bank. The area of analysis is related to two separate analytical areas composed of certain combinations of the Basel Matrix risk categories. The focus of interest is in the modelling of loss severity distributions in LDA models and in consideration of the power and character of dependences among the studied analytical areas. To model a single loss severity distribution, the authors used the approach based on extreme values theory EVT. GPD distribution was used to model the right tail. The t-Student copula function was used in the cases of consideration of power and character of dependences. The determined values describe the effects of the applied approach in relative scale.

Keywords

EN

operational risk; copula functions; GPD distribution; VaR

• Publisher: Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu
• Journal: Econometrics. Ekonometria. Advances in Applied Data Analytics
• Year: 2013
• Issue: 1(39)
• Pages: 133-143

Dates

published

2013

Contributors

author

Krzysztof Basiaga

• Uniwersytet Ekonomiczny w Katowicach

author

Tomasz Szkutnik

• Uniwersytet Ekonomiczny w Katowicach

References

• Chernobai A., Rachev S., Fabozzi F. (2007), Operational Risk. A Guide to Basel II Capital Requirements, Models and Analysis, Wiley & Sons, Hoboken, NJ.
• Cherubini U., Luciano E., Vecchiato W. (2004), Copula Methods in Finance, Wiley & Sons, Chichester.
• Di Clemente A., Romano C. (2004), A copula-extreme value theory approach for modelling operational risk, [in:] M. Cruz (ed.), Operational Risk Modelling and Analysis. Theory and Practice, Risk Books, London.
• Embrecht P., Kluppelberg C., Mikosch T. (1997), Modeling Extremal Events, Springer-Verlag, Berlin.
• Embrecht P., Hoing A., Juri A. (2003), Using copulae to bound the Value-at-Risk for functions of dependent risks, Finance and Stochastics 7.
• Klugman S., Panjer H., Willmot G. (2008), Loss Models from Data to Decisions, Wiley & Sons, Hobo-ken, NJ.