國立高雄大學圖資館 |

Language: English

Back

Statistical analysis of operational ...

Carita, Danilo.

Statistical analysis of operational risk data

Record Type:	Electronic resources : Monograph/item
Title/Author:	Statistical analysis of operational risk databy Giovanni De Luca, Danilo Carita, Francesco Martinelli.
Author:	De Luca, Giovanni.
other author:	Carita, Danilo.
Published:	Cham :Springer International Publishing :2020.
Description:	ix, 84 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Operational riskStatistics.
Online resource:	https://doi.org/10.1007/978-3-030-42580-7
ISBN:	9783030425807$q(electronic bk.)

Statistical analysis of operational risk data
De Luca, Giovanni.

Statistical analysis of operational risk data[electronic resource] /by Giovanni De Luca, Danilo Carita, Francesco Martinelli. - Cham :Springer International Publishing :2020. - ix, 84 p. :ill., digital ;24 cm. - SpringerBriefs in statistics,2191-544X. - SpringerBriefs in statistics..

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.

ISBN: 9783030425807$q(electronic bk.)

Standard No.: 10.1007/978-3-030-42580-7doiSubjects--Topical Terms:

862940
Operational risk
--Statistics.

LC Class. No.: HD61 / .D458 2020

Dewey Class. No.: 658.155

Statistical analysis of operational risk data
LDR:02113nmm a2200349 a 4500 001 575116
003 DE-He213
005 20200717095244.0
006 m d
007 cr nn 008maaau
008 201016s2020 sz s 0 eng d
020 $a 9783030425807$q(electronic bk.)
020 $a 9783030425791$q(paper)
024 7 $a 10.1007/978-3-030-42580-7 $2 doi
035 $a 978-3-030-42580-7
040 $a GP $c GP
041 0 $a eng
050 4 $a HD61 $b .D458 2020
072 7 $a PBT $2 bicssc
072 7 $a BUS061000 $2 bisacsh
072 7 $a PBT $2 thema
072 7 $a K $2 thema
082 0 4 $a 658.155 $2 23
090 $a HD61 $b .D366 2020
100 1 $a De Luca, Giovanni. $3 862937
245 1 0 $a Statistical analysis of operational risk data $h [electronic resource] / $c by Giovanni De Luca, Danilo Carita, Francesco Martinelli.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2020.
300 $a ix, 84 p. : $b ill., digital ; $c 24 cm.
490 1 $a SpringerBriefs in statistics, $x 2191-544X
505 0 $a 1 The Operational Risk -- 2 Identification of the Risk Classes -- 3 Severity Analysis -- 4 Frequency Analysis -- 5 Convolution and Risk Class Aggregation -- 6 Conclusions.
520 $a 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.
650 0 $a Operational risk $v Statistics. $3 862940
650 0 $a Risk management $3 217210
650 0 $a Statistics $x Methodology. $3 224891
650 1 4 $a Statistics for Business, Management, Economics, Finance, Insurance. $3 825914
650 2 4 $a Risk Management. $3 297189
650 2 4 $a Economic Theory/Quantitative Economics/Mathematical Methods. $3 731081
650 2 4 $a Financial Services. $3 747489
650 2 4 $a Applications of Mathematics. $3 273744
700 1 $a Carita, Danilo. $3 862938
700 1 $a Martinelli, Francesco. $3 862939
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
830 0 $a SpringerBriefs in statistics. $3 557771
856 4 0 $u https://doi.org/10.1007/978-3-030-42580-7
950 $a Mathematics and Statistics (Springer-11649)