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Low-bias simulation scheme for the Heston model by Inverse Gaussian approximation

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  • S. T. Tse
  • Justin W. L. Wan

Abstract

Fast and accurate sampling of conditional time-integrated variance in the Heston model is an important and challenging problem. We proved that this very complicated distribution converges to the moment-matched Inverse Gaussian distribution as the time interval goes to infinity. Leveraging on this theoretical result, we develop an efficient and accurate Inverse Gaussian approximation to sample conditional time-integrated variance. Numerical results demonstrate that our scheme compares favourably with state-of-the-art methods in accuracy given the same computational time for moderately path-dependent options.

Suggested Citation

  • S. T. Tse & Justin W. L. Wan, 2013. "Low-bias simulation scheme for the Heston model by Inverse Gaussian approximation," Quantitative Finance, Taylor & Francis Journals, vol. 13(6), pages 919-937, May.
    • Handle: RePEc:taf:quantf:v:13:y:2013:i:6:p:919-937
    DOI: 10.1080/14697688.2012.696678
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    Cited by:

    1. Ioannis Kyriakou & Panos K. Pouliasis & Nikos C. Papapostolou, 2016. "Jumps and stochastic volatility in crude oil prices and advances in average option pricing," Quantitative Finance, Taylor & Francis Journals, vol. 16(12), pages 1859-1873, December.
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