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Books > Reference & Interdisciplinary > Communication studies > Decision theory > Risk assessment
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Measuring Corporate Default Risk (Hardcover)
Loot Price: R2,415
Discovery Miles 24 150
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Measuring Corporate Default Risk (Hardcover)
Series: Clarendon Lectures in Finance
Expected to ship within 12 - 17 working days
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This book, based on the author's Clarendon Lectures in Finance,
examines the empirical behavior 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.
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