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320 pages. 10.25x7.50x1.25 inches. In Stock. This item is printed on demand. Codice articolo __1119143985
<b>The long-awaited, comprehensive guide to practical credit risk modeling</b> <p><i>Credit Risk Analytics</i> provides a targeted training guide for risk managers looking to efficiently build or validate in-house models for credit risk management. Combining theory with practice, this book walks you through the fundamentals of credit risk management and shows you how to implement these concepts using the SAS credit risk management program, with helpful code provided. Coverage includes data analysis and preprocessing, credit scoring; PD and LGD estimation and forecasting, low default portfolios, correlation modeling and estimation, validation, implementation of prudential regulation, stress testing of existing modeling concepts, and more, to provide a one-stop tutorial and reference for credit risk analytics. The companion website offers examples of both real and simulated credit portfolio data to help you more easily implement the concepts discussed, and the expert author team provides practical insight on this real-world intersection of finance, statistics, and analytics. <p>SAS is the preferred software for credit risk modeling due to its functionality and ability to process large amounts of data. This book shows you how to exploit the capabilities of this high-powered package to create clean, accurate credit risk management models. <ul> <li>Understand the general concepts of credit risk management</li> <li>Validate and stress-test existing models</li> <li>Access working examples based on both real and simulated data</li> <li>Learn useful code for implementing and validating models in SAS</li> </ul> <p>Despite the high demand for in-house models, there is little comprehensive training available; practitioners are left to comb through piece-meal resources, executive training courses, and consultancies to cobble together the information they need. This book ends the search by providing a comprehensive, focused resource backed by expert guidance. <i>Credit Risk Analytics</i> is the reference every risk manager needs to streamline the modeling process.
Informazioni sull?autore: <p><b>BART BAESENS</b> is a professor at KU Leuven (Belgium) and a lecturer at the University of Southampton (United Kingdom). <p><b>DANIEL RÖSCH</b> is a professor in business and management and chair in statistics and risk management at the University of Regensburg (Germany). <p><b>HARALD SCHEULE</b> is an associate professor of finance at the University of Technology Sydney (Australia) and a regional director of the Global Association of Risk Professionals.
Titolo: Credit Risk Analytics Measurement ...
Casa editrice: John Wiley & Sons Inc
Data di pubblicazione: 2016
Legatura: Hardcover
Condizione: Brand New
Da: medimops, Berlin, Germania
Condizione: very good. Gut/Very good: Buch bzw. Schutzumschlag mit wenigen Gebrauchsspuren an Einband, Schutzumschlag oder Seiten. / Describes a book or dust jacket that does show some signs of wear on either the binding, dust jacket or pages. Codice articolo M01119143985-V
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Da: medimops, Berlin, Germania
Condizione: as new. Wie neu/Like new. Codice articolo M01119143985-N
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Da: Books From California, Simi Valley, CA, U.S.A.
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Da: Chiron Media, Wallingford, Regno Unito
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Da: CitiRetail, Stevenage, Regno Unito
Hardcover. Condizione: new. Hardcover. The long-awaited, comprehensive guide to practical credit risk modeling Credit Risk Analytics provides a targeted training guide for risk managers looking to efficiently build or validate in-house models for credit risk management. Combining theory with practice, this book walks you through the fundamentals of credit risk management and shows you how to implement these concepts using the SAS credit risk management program, with helpful code provided. Coverage includes data analysis and preprocessing, credit scoring; PD and LGD estimation and forecasting, low default portfolios, correlation modeling and estimation, validation, implementation of prudential regulation, stress testing of existing modeling concepts, and more, to provide a one-stop tutorial and reference for credit risk analytics. The companion website offers examples of both real and simulated credit portfolio data to help you more easily implement the concepts discussed, and the expert author team provides practical insight on this real-world intersection of finance, statistics, and analytics. SAS is the preferred software for credit risk modeling due to its functionality and ability to process large amounts of data. This book shows you how to exploit the capabilities of this high-powered package to create clean, accurate credit risk management models. Understand the general concepts of credit risk managementValidate and stress-test existing modelsAccess working examples based on both real and simulated dataLearn useful code for implementing and validating models in SAS Despite the high demand for in-house models, there is little comprehensive training available; practitioners are left to comb through piece-meal resources, executive training courses, and consultancies to cobble together the information they need. This book ends the search by providing a comprehensive, focused resource backed by expert guidance. Credit Risk Analytics is the reference every risk manager needs to streamline the modeling process. The long-awaited, comprehensive guide to practical credit risk modeling Credit Risk Analytics provides a targeted training guide for risk managers looking to efficiently build or validate in-house models for credit risk management. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Codice articolo 9781119143987
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Da: California Books, Miami, FL, U.S.A.
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