000			01860nam a22003375i 4500
001			91266
005			20231026103945.0
010			_a978-3-030-42580-7 _dcompra
090			_a91266
100			_a20231023d2020 k||y0pory50 ba
101	0		_aeng
102			_aCH
200	1		_aStatistical analysis of operational risk data _bDocumento eletrónico _fby Giovanni De Luca, Danilo Carità, Francesco Martinelli
210			_aCham _cSpringer International Publishing _cSpringer _d2020
215			_aIX, 84 p. _cil.
225	2		_aSpringerBriefs in Statistics
303			_aThis 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.
606			_aStatistics
606			_aFinancial risk management
606			_aEconometrics
606			_aFinancial services industry
606			_aMathematics
680			_aQA276-280
700	1		_aDe Luca _bGiovanni
701	1		_aCarità _bDanilo
701	1		_aMartinelli _bFrancesco
801		0	_aPT _gRPC
856	4		_uhttps://doi.org/10.1007/978-3-030-42580-7
942			_2lcc _cF _n0