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Credit Risk: Pricing, Measurement, and Management (Princeton Series in Finance)

Amazon.com Price:  $42.09 (as of 12/05/2019 19:22 PST- Details)

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Description

In this book, two of The us’s leading economists give you the first integrated remedy of the conceptual, practical, and empirical foundations for credit risk pricing and risk measurement. Masterfully applying theory to practice, Darrell Duffie and Kenneth Singleton model credit risk for the purpose of measuring portfolio risk and pricing defaultable bonds, credit derivatives, and other securities exposed to credit risk. The methodological rigor, scope, and sophistication of their cutting-edge account is unparalleled, and its singularly in-depth remedy of pricing and credit derivatives further illuminates an issue that has drawn much attention in an era when financial institutions internationally are revising their credit management strategies.

Duffie and Singleton offer critical assessments of alternative approaches to credit-risk modeling, at the same time as highlighting the strengths and weaknesses of current practice. Their approach blends in-depth discussions of the conceptual foundations of modeling with extensive analyses of the empirical properties of such credit-related time series as default probabilities, recoveries, ratings transitions, and yield spreads. Both the “structura” and “reduced-form” approaches to pricing defaultable securities are presented, and their comparative fits to historical data are assessed. The authors also provide a comprehensive remedy of the pricing of credit derivatives, including credit swaps, collateralized debt obligations, credit guarantees, lines of credit, and spread options. Not least, they describe certain enhancements to current pricing and management practices that, they argue, will better position financial institutions for future changes within the financial markets.

Credit Risk is an indispensable resource for risk managers, traders or regulators coping with financial products with a significant credit risk component, in addition to for academic researchers and students.

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