Using an Euler discretization to simulate a mean-reverting CEV process gives rise to the problem that while the process itself is guaranteed to be nonnegative, the discretization is not. Although an exact and efficient simulation algorithm exists for this process, at present this is not the case for the CEV-SV stochastic volatility model, with the Heston model as a special case, where the variance is modelled as a mean-reverting CEV process. Consequently, when using an Euler discretization, one must carefully think about how to fix negative variances. Our contribution is threefold. Firstly, we unify all Euler fixes into a single general framework. Secondly, we introduce the new full truncation scheme, tailored to minimize the positive bias found when pricing European options. Thirdly and finally, we numerically compare all Euler fixes to recent quasi-second order schemes of Kahl and Jckel, and Ninomiya and Victoir, as well as to the exact scheme of Broadie and Kaya. The choice of fix is found to be extremely important. The full truncation scheme outperforms all considered biased schemes in terms of bias and root-mean-squared error

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Keywords CEV process, Euler-Maruyama, Heston, boundary behaviour, discretization, square root process, stochastic voladility, strong convergence, weak convergence
Persistent URL dx.doi.org/10.1080/14697680802392496, hdl.handle.net/1765/18571
Citation
Lord, R., Koekkoek, R., & van Dijk, D.J.C.. (2010). A comparison of biased simulation schemes for stochastic volatility models. Quantitative Finance, 10(2), 177–194. doi:10.1080/14697680802392496