Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
EUR 36,55
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In den WarenkorbBuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - The devastating impacts of the recent global financial crisis underscore the need for both financial institutions and banking supervision to develop more appropriate credit risk models to ensure the stability of the financial system. This work contributes to quantitative credit portfolio risk modeling in three ways. First, it introduces a general credit portfolio modeling concept that comprises specific credit risk management models as special cases. Second, analytical techniques are presented for specifying asset correlations in a credit portfolio through systematic factors. Finally, a new approach for clustering of obligors in a credit portfolio is proposed using threshold accepting, a stochastic optimization technique. In particular, a computationally tractable technique to validate ex-post the precision of the clustering system is suggested and applied to a real world retail credit portfolio. The contributions of this book should provide benefit to practitioners, academics and graduate students in the field of financial risk management.
Verlag: Peter Lang, Peter Lang Mär 2011, 2011
ISBN 10: 3631611714 ISBN 13: 9783631611715
Sprache: Englisch
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
EUR 36,55
Währung umrechnenAnzahl: 2 verfügbar
In den WarenkorbBuch. Zustand: Neu. Neuware -The devastating impacts of the recent global financial crisis underscore the need for both financial institutions and banking supervision to develop more appropriate credit risk models to ensure the stability of the financial system. This work contributes to quantitative credit portfolio risk modeling in three ways. First, it introduces a general credit portfolio modeling concept that comprises specific credit risk management models as special cases. Second, analytical techniques are presented for specifying asset correlations in a credit portfolio through systematic factors. Finally, a new approach for clustering of obligors in a credit portfolio is proposed using threshold accepting, a stochastic optimization technique. In particular, a computationally tractable technique to validate ex-post the precision of the clustering system is suggested and applied to a real world retail credit portfolio. The contributions of this book should provide benefit to practitioners, academics and graduate students in the field of financial risk management. 122 pp. Englisch.