Quantitative models for operational risk: Extremes,dependence and aggregation |
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| Affiliation: | 1. Laboratory of Actuarial and Financial Sciences (LSAF, EA2429), Institute of Financial and Insurance Sciences, University Claude Bernard Lyon 1, France;2. Laboratory Research for Economy, Management and Quantitative Finance, Institute of High Commercial Studies of Sousse, Tunisia;1. Brunel Business School, Brunel University London, Kingston Lane, Uxbridge, London UB8 3PH, UK;2. Faculty of Commerce, Mansoura University, Mansoura, Egypt;3. Department of Accounting, Centre for Research in Accounting, Accountability and Governance, Southampton Business School, University of Southampton, Southampton SO17 1BJ, UK;4. Lancashire School of Business and Enterprise, University of Central Lancashire, Preston PR1 2HE, UK |
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| Abstract: | Due to the new regulatory guidelines known as Basel II for banking and Solvency 2 for insurance, the financial industry is looking for qualitative approaches to and quantitative models for operational risk. Whereas a full quantitative approach may never be achieved, in this paper we present some techniques from probability and statistics which no doubt will prove useful in any quantitative modelling environment. The techniques discussed are advanced peaks over threshold modelling, the construction of dependent loss processes and the establishment of bounds for risk measures under partial information, and can be applied to other areas of quantitative risk management.1 |
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