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Invite colleaguesAnalytic models of the receiver operating characteristic curve: Applications to credit rating model validation
Abstract
In this paper, the authors use the concept of the population receiver operating characteristic (ROC) curve to build analytic models of ROC curves. Information about the population properties can be used to gain greater accuracy of estimation relative to the non-parametric methods currently in vogue. If used properly, this is particularly helpful in some situations where the number of sick loans is rather small, a situation frequently met in practice and in periods of benign macroeconomic background.
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Author's Biography
Steve Satchell is the Academic Advisor to many financial institutions; a Fellow of Trinity College, Cambridge; the Reader in Financial Econometrics at Cambridge University; and a visiting Professor at Birkbeck College, CASS Business School and UTS, Sydney. He specialises in econometrics and finances and has published over 120 journal articles. He has PhDs from Cambridge University and the LSE, and is an Honorary Actuary. Steve is also the Editor of the Journal of Asset Management and Derivatives and Derivatives, Use, Trading and Regulation.
Wei Xia is a PhD candidate in quantitative finance at Birkbeck College and visiting lecturer at the University of International Business and Economics, Beijing. Wei is also a researcher at Aspect Capital Management in London. Previously he was an executive consultant with the Risk and Capital Group, Pricewaterhouse Coopers LLP UK, responsible for cross-asset class derivative valuations and advisor on quantitative market risk, credit risk and operational risk measurement and management. Prior to this, Wei was a quantitative developer at Winton Capital Management, London, responsible for designing and developing an in-house risk measurement and reporting system.
Citation
Satchell, Steve and Xia, Wei (2007, December 1). Analytic models of the receiver operating characteristic curve: Applications to credit rating model validation. In the Journal of Risk Management in Financial Institutions, Volume 1, Issue 1. https://doi.org/10.69554/DTTL8705.Publications LLP