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＜電子ブック＞
Statistical Analysis of Operational Risk Data / by Giovanni De Luca, Danilo Carità, Francesco Martinelli
(SpringerBriefs in Statistics. ISSN:21915458)

版	1st ed. 2020.
出版者	(Cham : Springer International Publishing : Imprint: Springer)
出版年	2020
本文言語	英語
大きさ	IX, 84 p. 68 illus., 44 illus. in color : online resource
著者標目	*De Luca, Giovanni author Carità, Danilo author Martinelli, Francesco author SpringerLink (Online service)
件　名	LCSH:Statistics  LCSH:Financial risk management LCSH:Econometrics LCSH:Financial services industry LCSH:Mathematics FREE:Statistics in Business, Management, Economics, Finance, Insurance FREE:Risk Management FREE:Quantitative Economics FREE:Financial Services FREE:Applications of Mathematics
一般注記	1 The Operational Risk -- 2 Identification of the Risk Classes -- 3 Severity Analysis -- 4 Frequency Analysis -- 5 Convolution and Risk Class Aggregation -- 6 Conclusions This concise book for practitioners presents the statistical analysis of operational risk, which is considered the most relevant source of bank risk, after market and credit risk. The book shows that a careful statistical analysis can improve the results of the popular loss distribution approach. The authors identify the risk classes by applying a pooling rule based on statistical tests of goodness-of-fit, use the theory of the mixture of distributions to analyze the loss severities, and apply copula functions for risk class aggregation. Lastly, they assess operational risk data in order to estimate the so-called capital-at-risk that represents the minimum capital requirement that a bank has to hold. The book is primarily intended for quantitative analysts and risk managers, but also appeals to graduate students and researchers interested in bank risks HTTP:URL=https://doi.org/10.1007/978-3-030-42580-7

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