An Accurate Solution for Credit Valuation Adjustment (CVA) and Wrong Way Risk
Principal Investigator(s): View help for Principal Investigator(s) Tim Xiao, BMO
Version: View help for Version V1
Project Citation:
Xiao, Tim. An Accurate Solution for Credit Valuation Adjustment (CVA) and Wrong Way Risk. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2020-05-23. https://doi.org/10.3886/E119581V1
Project Description
Summary:
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This paper presents a Least Square Monte
Carlo approach for accurately calculating credit value adjustment (CVA). In contrast to previous studies, the model relies on the probability distribution of
a default time/jump rather than the default time itself, as the default time is
usually inaccessible. As such, the model can achieve a high order of accuracy
with a relatively easy implementation. We find that the valuation of a
defaultable derivative is normally determined via backward induction when their
payoffs could be positive or negative. Moreover, the model can naturally
capture wrong or right way risk.
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