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The analytics of risk model validation[electronic resource] /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
杜威分類號:	658.155015118
書名/作者:	The analytics of risk model validation/ edited by George Christodoulakis, Stephen Satchell.
其他作者:	Christodoulakis, George.
出版者:	Amsterdam ; : Elsevier/Academic Press,, c2008.
面頁冊數:	xi, 201 p. ;; 24 cm.
叢書名:	Quantitative finance series
標題:	Risk management - Mathematical models.
ISBN:	9780750681582
ISBN:	0750681586
書目註:	Includes bibliographical references and index.
內容註:	Contents -- Chapter 1 Determinants of small business default, Sumit Agarwal, Souphala Chomsisengphet and Chunlin Liu -- Chapter 2 Validation of stress testing models, Jospeh L. Breeden -- Chapter 3 The validity of credit risk model validation methods, George Christodoulakis and Stephen Satchell -- Chapter 4 A moment-based procedure for evaluating risk forecasting models, Kevin Dowd -- -- Chpater 5 Measuring concentration risk in credit portfolios, Klaus Duellmann -- Chapter 6 A simple method for regulators to cross-check operational risk loss models for banks, Wayne Holland and ManMohan S. Sodhi -- Chapter 7 Of the credibility of mapping and bencmarking credit risk estimates for internal rating systems, Vichett Oung -- Chapter 8 Analytic models of the ROC curve: Applications to credit rating model validation, Stephen Satchell and Wei Xia -- Chapter 9 The validation of the equity portfolio risk models, Stephen Satchell -- Chapter 10 Dynamic risk analysis and risk model evaluation, Gunter Schwarz and Christoph Kessler -- Chapter 11 Validation of internal rating systems and PD esitmates, Dirk Tasche -- Index.
摘要、提要註:	Risk model validation is an emerging and important area of research, and has arisen because of Basel I and II. These regulatory initiatives require trading institutions and lending institutions to compute their reserve capital in a highly analytic way, based on the use of internal risk models. It is part of the regulatory structure that these risk models be validated both internally and externally, and there is a great shortage of information as to best practise. Editors Christodoulakis and Satchell collect papers that are beginning to appear by regulators, consultants, and academics, to provide the first collection that focuses on the quantitative side of model validation. The book covers the three main areas of risk: Credit Risk and Market and Operational Risk. Risk model validation is a requirement of Basel I and II The first collection of papers in this new and developing area of research *International authors cover model validation in credit, market, and operational risk.
電子資源:	An electronic book accessible through the World Wide Web; click for information
電子資源:	http://www.loc.gov/catdir/enhancements/fy0833/2008297532-d.html

The analytics of risk model validation[electronic resource] /
The analytics of risk model validation[electronic resource] /edited by George Christodoulakis, Stephen Satchell. - 1st ed. - Amsterdam ;Elsevier/Academic Press,c2008. - xi, 201 p. ;24 cm. - Quantitative finance series.

Includes bibliographical references and index.

Contents -- Chapter 1 Determinants of small business default, Sumit Agarwal, Souphala Chomsisengphet and Chunlin Liu -- Chapter 2 Validation of stress testing models, Jospeh L. Breeden -- Chapter 3 The validity of credit risk model validation methods, George Christodoulakis and Stephen Satchell -- Chapter 4 A moment-based procedure for evaluating risk forecasting models, Kevin Dowd -- -- Chpater 5 Measuring concentration risk in credit portfolios, Klaus Duellmann -- Chapter 6 A simple method for regulators to cross-check operational risk loss models for banks, Wayne Holland and ManMohan S. Sodhi -- Chapter 7 Of the credibility of mapping and bencmarking credit risk estimates for internal rating systems, Vichett Oung -- Chapter 8 Analytic models of the ROC curve: Applications to credit rating model validation, Stephen Satchell and Wei Xia -- Chapter 9 The validation of the equity portfolio risk models, Stephen Satchell -- Chapter 10 Dynamic risk analysis and risk model evaluation, Gunter Schwarz and Christoph Kessler -- Chapter 11 Validation of internal rating systems and PD esitmates, Dirk Tasche -- Index.

Risk model validation is an emerging and important area of research, and has arisen because of Basel I and II. These regulatory initiatives require trading institutions and lending institutions to compute their reserve capital in a highly analytic way, based on the use of internal risk models. It is part of the regulatory structure that these risk models be validated both internally and externally, and there is a great shortage of information as to best practise. Editors Christodoulakis and Satchell collect papers that are beginning to appear by regulators, consultants, and academics, to provide the first collection that focuses on the quantitative side of model validation. The book covers the three main areas of risk: Credit Risk and Market and Operational Risk. *Risk model validation is a requirement of Basel I and II *The first collection of papers in this new and developing area of research *International authors cover model validation in credit, market, and operational risk.

Electronic reproduction.
Amsterdam :
Elsevier Science & Technology,
2008.

Mode of access: World Wide Web.

ISBN: 9780750681582

Source: 133772:133898Elsevier Science & Technologyhttp://www.sciencedirect.comSubjects--Topical Terms:

367082
Risk management
--Mathematical models.Index Terms--Genre/Form:

336502
Electronic books.

LC Class. No.: HD61 / .A525 2008eb

Dewey Class. No.: 658.155015118

The analytics of risk model validation[electronic resource] /
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300 $a xi, 201 p. ; $c 24 cm.
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504 $a Includes bibliographical references and index.
505 0 $a Contents -- Chapter 1 Determinants of small business default, Sumit Agarwal, Souphala Chomsisengphet and Chunlin Liu -- Chapter 2 Validation of stress testing models, Jospeh L. Breeden -- Chapter 3 The validity of credit risk model validation methods, George Christodoulakis and Stephen Satchell -- Chapter 4 A moment-based procedure for evaluating risk forecasting models, Kevin Dowd -- -- Chpater 5 Measuring concentration risk in credit portfolios, Klaus Duellmann -- Chapter 6 A simple method for regulators to cross-check operational risk loss models for banks, Wayne Holland and ManMohan S. Sodhi -- Chapter 7 Of the credibility of mapping and bencmarking credit risk estimates for internal rating systems, Vichett Oung -- Chapter 8 Analytic models of the ROC curve: Applications to credit rating model validation, Stephen Satchell and Wei Xia -- Chapter 9 The validation of the equity portfolio risk models, Stephen Satchell -- Chapter 10 Dynamic risk analysis and risk model evaluation, Gunter Schwarz and Christoph Kessler -- Chapter 11 Validation of internal rating systems and PD esitmates, Dirk Tasche -- Index.
520 $a Risk model validation is an emerging and important area of research, and has arisen because of Basel I and II. These regulatory initiatives require trading institutions and lending institutions to compute their reserve capital in a highly analytic way, based on the use of internal risk models. It is part of the regulatory structure that these risk models be validated both internally and externally, and there is a great shortage of information as to best practise. Editors Christodoulakis and Satchell collect papers that are beginning to appear by regulators, consultants, and academics, to provide the first collection that focuses on the quantitative side of model validation. The book covers the three main areas of risk: Credit Risk and Market and Operational Risk. *Risk model validation is a requirement of Basel I and II *The first collection of papers in this new and developing area of research *International authors cover model validation in credit, market, and operational risk.
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