LEADER 03921nam 22007095 450 001 996418279803316 005 20200629133609.0 010 $a3-030-42580-0 024 7 $a10.1007/978-3-030-42580-7 035 $a(CKB)4100000010473890 035 $a(DE-He213)978-3-030-42580-7 035 $a(MiAaPQ)EBC6121796 035 $a(PPN)242979912 035 $a(EXLCZ)994100000010473890 100 $a20200224d2020 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aStatistical Analysis of Operational Risk Data $b[electronic resource] /$fby Giovanni De Luca, Danilo Caritā, Francesco Martinelli 205 $a1st ed. 2020. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2020. 215 $a1 online resource (IX, 84 p. 68 illus., 44 illus. in color.) 225 1 $aSpringerBriefs in Statistics,$x2191-544X 311 $a3-030-42579-7 327 $a1 The Operational Risk -- 2 Identification of the Risk Classes -- 3 Severity Analysis -- 4 Frequency Analysis -- 5 Convolution and Risk Class Aggregation -- 6 Conclusions. 330 $aThis concise book for practitioners presents the statistical analysis of operational risk, which is considered the most relevant source of bank risk, after market and credit risk. The book shows that a careful statistical analysis can improve the results of the popular loss distribution approach. The authors identify the risk classes by applying a pooling rule based on statistical tests of goodness-of-fit, use the theory of the mixture of distributions to analyze the loss severities, and apply copula functions for risk class aggregation. Lastly, they assess operational risk data in order to estimate the so-called capital-at-risk that represents the minimum capital requirement that a bank has to hold. The book is primarily intended for quantitative analysts and risk managers, but also appeals to graduate students and researchers interested in bank risks. 410 0$aSpringerBriefs in Statistics,$x2191-544X 606 $aStatistics  606 $aRisk management 606 $aEconomic theory 606 $aBank marketing 606 $aApplied mathematics 606 $aEngineering mathematics 606 $aStatistics for Business, Management, Economics, Finance, Insurance$3https://scigraph.springernature.com/ontologies/product-market-codes/S17010 606 $aRisk Management$3https://scigraph.springernature.com/ontologies/product-market-codes/612040 606 $aEconomic Theory/Quantitative Economics/Mathematical Methods$3https://scigraph.springernature.com/ontologies/product-market-codes/W29000 606 $aFinancial Services$3https://scigraph.springernature.com/ontologies/product-market-codes/626000 606 $aApplications of Mathematics$3https://scigraph.springernature.com/ontologies/product-market-codes/M13003 615 0$aStatistics . 615 0$aRisk management. 615 0$aEconomic theory. 615 0$aBank marketing. 615 0$aApplied mathematics. 615 0$aEngineering mathematics. 615 14$aStatistics for Business, Management, Economics, Finance, Insurance. 615 24$aRisk Management. 615 24$aEconomic Theory/Quantitative Economics/Mathematical Methods. 615 24$aFinancial Services. 615 24$aApplications of Mathematics. 676 $a519.5 700 $aDe Luca$b Giovanni$4aut$4http://id.loc.gov/vocabulary/relators/aut$077549 702 $aCaritā$b Danilo$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aMartinelli$b Francesco$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996418279803316 996 $aStatistical Analysis of Operational Risk Data$92369397 997 $aUNISA