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An Accurate Solution for Credit Valuation Adjustment (CVA) and Wrong Way Risk

Version
1
Resource Type
Dataset
Creator
  • Xiao, Tim (BMO)
Publication Date
2020-05-23
Description
  • Abstract

    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.
Availability
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Update Metadata: 2020-05-23 | Issue Number: 1 | Registration Date: 2020-05-23

Xiao, Tim (2020): An Accurate Solution for Credit Valuation Adjustment (CVA) and Wrong Way Risk. Version: 1. ICPSR - Interuniversity Consortium for Political and Social Research. Dataset. https://doi.org/10.3886/E119581V1