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Statistical analysis of operational risk data
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. Th...
Autores principales: | , , |
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Lenguaje: | eng |
Publicado: |
Springer
2020
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Materias: | |
Acceso en línea: | https://dx.doi.org/10.1007/978-3-030-42580-7 http://cds.cern.ch/record/2711894 |
_version_ | 1780965259898519552 |
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author | De Luca, Giovanni Carità, Danilo Martinelli, Francesco |
author_facet | De Luca, Giovanni Carità, Danilo Martinelli, Francesco |
author_sort | De Luca, Giovanni |
collection | CERN |
description | 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. |
id | cern-2711894 |
institution | Organización Europea para la Investigación Nuclear |
language | eng |
publishDate | 2020 |
publisher | Springer |
record_format | invenio |
spelling | cern-27118942021-04-21T18:09:24Zdoi:10.1007/978-3-030-42580-7http://cds.cern.ch/record/2711894engDe Luca, GiovanniCarità, DaniloMartinelli, FrancescoStatistical analysis of operational risk dataMathematical Physics and MathematicsThis 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.Springeroai:cds.cern.ch:27118942020 |
spellingShingle | Mathematical Physics and Mathematics De Luca, Giovanni Carità, Danilo Martinelli, Francesco Statistical analysis of operational risk data |
title | Statistical analysis of operational risk data |
title_full | Statistical analysis of operational risk data |
title_fullStr | Statistical analysis of operational risk data |
title_full_unstemmed | Statistical analysis of operational risk data |
title_short | Statistical analysis of operational risk data |
title_sort | statistical analysis of operational risk data |
topic | Mathematical Physics and Mathematics |
url | https://dx.doi.org/10.1007/978-3-030-42580-7 http://cds.cern.ch/record/2711894 |
work_keys_str_mv | AT delucagiovanni statisticalanalysisofoperationalriskdata AT caritadanilo statisticalanalysisofoperationalriskdata AT martinellifrancesco statisticalanalysisofoperationalriskdata |