Statistical analysis of operational risk data
De Luca, Giovanni
Statistical analysis of operational risk data [Documento eletrónico] / by Giovanni De Luca, Danilo Carità, Francesco Martinelli. - Cham : Springer International Publishing : Springer , 2020 . - IX, 84 p. : il.. - (SpringerBriefs in Statistics) 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.
Clicar aqui para aceder a um recurso externo
ISBN 978-3-030-42580-7
Statistics
Financial risk management
Econometrics
Financial services industry
Mathematics
LCC QA276-280
Statistical analysis of operational risk data [Documento eletrónico] / by Giovanni De Luca, Danilo Carità, Francesco Martinelli. - Cham : Springer International Publishing : Springer , 2020 . - IX, 84 p. : il.. - (SpringerBriefs in Statistics) 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.
Clicar aqui para aceder a um recurso externo
ISBN 978-3-030-42580-7
Statistics
Financial risk management
Econometrics
Financial services industry
Mathematics
LCC QA276-280
