東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Statistical analysis of operational ...

De Luca, Giovanni.

Linked to FindBook

Google Book

Amazon

博客來

Statistical analysis of operational risk data

Record Type:	Electronic resources : Monograph/item
Title/Author:	Statistical analysis of operational risk data/ by 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.
[NT 15003449]:	1 The Operational Risk -- 2 Identification of the Risk Classes -- 3 Severity Analysis -- 4 Frequency Analysis -- 5 Convolution and Risk Class Aggregation -- 6 Conclusions.
Contained By:	Springer eBooks
Subject:	Operational risk - Statistics. -
Online resource:	https://doi.org/10.1007/978-3-030-42580-7
ISBN:	9783030425807

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

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

3448832
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 2216471
003 DE-He213
005 20200717095244.0
006 m d
007 cr nn 008maaau
008 201120s2020 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 3448829
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 3448832
650 0 $a Risk management $v Statistics. $3 3448833
650 0 $a Statistics $x Methodology. $3 536915
650 1 4 $a Statistics for Business, Management, Economics, Finance, Insurance. $3 3382132
650 2 4 $a Risk Management. $3 608953
650 2 4 $a Economic Theory/Quantitative Economics/Mathematical Methods. $3 2162305
650 2 4 $a Financial Services. $3 2194957
650 2 4 $a Applications of Mathematics. $3 890893
700 1 $a Carita, Danilo. $3 3448830
700 1 $a Martinelli, Francesco. $3 3448831
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
830 0 $a SpringerBriefs in statistics. $3 1565658
856 4 0 $u https://doi.org/10.1007/978-3-030-42580-7
950 $a Mathematics and Statistics (Springer-11649)