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A Comparison of Biased Simulation Schemes for Stochastic Volatility Models

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Author Info
Roger Lord () (Erasmus Universiteit Rotterdam, and Rabobank)
Remmert Koekkoek () (Robeco Alternative Investments)
Dick van Dijk () (Faculty of Economics, Erasmus Universiteit Rotterdam)

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Abstract

When using an Euler discretisation to simulate a mean-reverting square root process, one runs into the problem that while the process itself is guaranteed to be nonnegative, the discretisation is not. Although an exact and efficient simulation algorithm exists for this process, at present this is not the case for the Heston stochastic volatility model, where the variance is modelled as a square root process. Consequently, when using an Euler discretisation, 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 minimise the upward bias found when pricing European options. Thirdly and finally, we numerically compare all Euler fixes to a recent quasi-second order scheme of Kahl and Jäckel and the exact scheme of Broadie and Kaya. The choice of fix is found to be extremely important. The full truncation scheme by far outperforms all biased schemes in terms of bias, root-mean-squared error, and hence should be the preferred discretisation method for simulation of the Heston model and extensions thereof.

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Publisher Info
Paper provided by Tinbergen Institute in its series Tinbergen Institute Discussion Papers with number 06-046/4.

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Date of creation: 18 May 2006
Date of revision: 07 Jun 2007
Handle: RePEc:dgr:uvatin:20060046

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Web page: http://www.tinbergen.nl/

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Related research
Keywords: Stochastic volatility Heston square root process Euler-Maruyama discretisation strong convergence weak convergence boundary behaviour

Find related papers by JEL classification:
C63 - Mathematical and Quantitative Methods - - Mathematical Methods and Programming - - - Computational Techniques
G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing

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  1. Roger Lord & Christian Kahl, 2006. "Why the Rotation Count Algorithm works," Tinbergen Institute Discussion Papers 06-065/2, Tinbergen Institute. [Downloadable!]
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