2017
Efficient estimation of sensitivities for counterparty credit risk with the finite difference Monte Carlo method
Publication
Publication
Journal of Computational Finance , Volume 21 - Issue 1 p. 1- 31
According to Basel III, financial institutions have to charge a credit valuation adjustment
(CVA) to account for a possible counterparty default. Calculating this measure
and its sensitivities is one of the biggest challenges in risk management. Here, we
introduce an efficient method for the estimation of CVA and its sensitivities for a
portfolio of financial derivatives. We use the finite difference Monte Carlo (FDMC)
method to measure exposure profiles and consider the computationally challenging
case of foreign exchange barrier options in the context of the Black–Scholes as well as
the Heston stochastic volatility model, with and without stochastic domestic interest
rate, for a wide range of parameters. In the case of a fixed domestic interest rate, our
results show that FDMC is an accurate method compared with the semi-analytic COS
method and, advantageously, can compute multiple options on one grid. In the more
general case of a stochastic domestic interest rate, we show that we can accurately
compute exposures of discontinuous one-touch options by using a linear interpolation
technique as well as sensitivities with respect to initial interest rate and variance. This
paves the way for real portfolio level risk analysis.
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Risk Publications | |
doi.org/10.21314/JCF.2016.325 | |
Journal of Computational Finance | |
de Graaf, K., Kandhai, B. D., & Sloot, P. (2017). Efficient estimation of sensitivities for counterparty credit risk with the finite difference Monte Carlo method. Journal of Computational Finance, 21(1), 1–31. doi:10.21314/JCF.2016.325 |