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Books > Reference & Interdisciplinary > Communication studies > Decision theory > Risk assessment
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Measuring Corporate Default Risk (Paperback)
Loot Price: R766
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Measuring Corporate Default Risk (Paperback)
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 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.
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