Abstract
This paper studies the problem of default correlation. We first
introduce a random variable called "time-until- default" to denote
the survival time of each defaultable entity or financial
instrument, and define the default correlation between two credit
risks as the correlation coefficient between their survival times.
Then we argue why a copula function approach should be used to
specify the joint distribution of survival times after marginal
distributions of survival times are derived from market
information, such as risky bond prices or asset swap spreads. The
definition and some basic properties of copula functions are given.
We show that the current CreditMetrics approach to default
correlation through asset correlation is equivalent to using a
normal copula function. Finally, we give some numerical examples to
illustrate the use of copula functions in the valuation of some
credit derivatives, such as credit default swaps and
first-to-default contracts. |
