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Measuring Corporate Default Risk (Clarendon Lectures in Finance) - Softcover
Book 3 of 4: Clarendon Lectures in Finance
Synopsis
Based on the author's Clarendon Lectures in Finance, this book develops and implements statistical methods for modelling corporate credit risk.
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About the Author
Darrell Duffie, The Adams Distinguished Professor of Management and Professor of Finance, Stanford Graduate School of Business
Darrell Duffie is the The Adams Distinguished Professor of Management and Professor of Finance at Stanford Graduate School of Business and has been writing about financial markets since 1984. He is a fellow and member of the Council of the Econometric Society, a research fellow of the National Bureau of Economic Research, and a fellow of the American Academy of Arts and Sciences. Duffie was the 2009 president of the American Finance Association. In 2014, he chaired the Market Participants Group, charged by the Financial Stability Board with recommending reforms to Libor, Euribor, and other interest rate benchmarks. Duffie's recent books include How Big Banks Fail (Princeton University Press, 2010), Measuring Corporate Default Risk (Oxford University Press, 2011), and Dark Markets (Princeton University Press, 2012).
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Measuring Corporate Default Risk
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Measuring Corporate Default Risk (Clarendon Lectures in Finance)
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Measuring Corporate Default Risk
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Measuring Corporate Default Risk
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Measuring Corporate Default Risk
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Measuring Corporate Default Risk (eng)
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Measuring Corporate Default Risk (Paperback)
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ISBN 10: 0199279241
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Paperback. Condition: new. Paperback. This book, based on the author's Clarendon Lectures in Finance, examines the empirical behaviour of corporate default risk. A new and unified statistical methodology for default prediction, based on stochastic intensity modeling, is explained and implemented with data on U.S. public corporations since 1980. Special attention is given to the measurement of correlation of default risk across firms. The underlying work was developed in a series of collaborations over roughly the past decade with Sanjiv Das, Andreas Eckner, Guillaume Horel, Nikunj Kapadia, Leandro Saita, and Ke Wang. Where possible, the content based on methodology has been separated from the substantive empirical findings, in order to provide access to the latter for those less focused on the mathematical foundations.A key finding is that corporate defaults are more clustered in time than would be suggested by their exposure to observable common or correlated risk factors. The methodology allows for hidden sources of default correlation, which are particularly important to include when estimating the likelihood that a portfolio of corporate loans will suffer large default losses. The data also reveal that a substantial amount of power for predicting the default of a corporation can be obtained from the firm's "distance to default," a volatility-adjusted measure of leverage that is the basis of the theoretical models of corporate debt pricing of Black, Scholes, and Merton. The findings are particularly relevant in the aftermath of the financial crisis, which revealed a lack of attention to the proper modelling of correlation of default risk across firms. Based on the author's Clarendon Lectures in Finance, this book develops and implements statistical methods for modelling corporate credit risk. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9780199279241
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Measuring Corporate Default Risk
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