Frachot, Antoine and Roncalli, Thierry and Salomon, Eric (2004): The Correlation Problem in Operational Risk. Published in: Operational Risk (May 2004)

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Abstract
This paper demonstrates that aggregate losses are necessarily low as long as we remain under the standard assumptions of LDA models. Moreover empirical findings show that the correlation between two aggregate losses is typically below 5%, which opens a wide scope for large diversification effects, much larger than those the Basel Committee seems to have in mind. In other words, summing up capital charges is in substantial contradiction with the type of correlation consistent with the standard LDA model.
Item Type:  MPRA Paper 

Original Title:  The Correlation Problem in Operational Risk 
Language:  English 
Keywords:  operational risk; LDA model; severity correlation; frequency correlation; aggregate loss correlation; 
Subjects:  C  Mathematical and Quantitative Methods > C0  General > C01  Econometrics 
Item ID:  38052 
Depositing User:  Thierry Roncalli 
Date Deposited:  12. Apr 2012 12:48 
Last Modified:  09. Sep 2015 04:25 
References:  Principles for the Homehost Recognition of AMA Operational Risk Capital, Basel Committee on Banking Supervision, January 2004 Evans, M., N. Hastings and B. Peacock [1993], Statistical Distributions, John Wiley & Sons Feller, W. [1971], An Introduction to Probability Theory and Its Applications, Volume II, second edition, John Wiley & Sons Frachot, A., P. Georges and T. Roncalli [2001], Loss distribution approach for operational risk, Working Paper, Crédit Lyonnais, Groupe de Recherche Opérationnelle Frachot, A., O. Moudoulaud and T. Roncalli [2003], Loss distribution approach in practice, in M. Ong (ed.), The Basel Handbook: A Guide for Financial Practitioners, Risk Books Johnson, N.L., S. Kotz and N. Balakrishnan [1997], Discrete Multivariate Distributions, Wiley Series in Probability and Statistics, John Wiley & Sons Klugman, S.A., H.H. Panjer and G.E. Willmot [1998], Loss Models: From Data to Decisions, Wiley Series in Probability and Mathematical Statistics, John Wiley \& Sons 
URI:  https://mpra.ub.unimuenchen.de/id/eprint/38052 