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Conditional sampling for barrier option pricing under the Heston model

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  • Nico Achtsis
  • Ronald Cools
  • Dirk Nuyens

Abstract

We propose a quasi-Monte Carlo algorithm for pricing knock-out and knock-in barrier options under the Heston (1993) stochastic volatility model. This is done by modifying the LT method from Imai and Tan (2006) for the Heston model such that the first uniform variable does not influence the stochastic volatility path and then conditionally modifying its marginals to fulfill the barrier condition(s). We show this method is unbiased and never does worse than the unconditional algorithm. Additionally the conditioning is combined with a root finding method to also force positive payouts. The effectiveness of this method is shown by extensive numerical results.

Suggested Citation

  • Nico Achtsis & Ronald Cools & Dirk Nuyens, 2012. "Conditional sampling for barrier option pricing under the Heston model," Papers 1207.6566, arXiv.org, revised Dec 2012.
    • Handle: RePEc:arx:papers:1207.6566
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    References listed on IDEAS

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    1. Alexander Van Haastrecht & Antoon Pelsser, 2010. "Efficient, Almost Exact Simulation Of The Heston Stochastic Volatility Model," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 13(01), pages 1-43.
    2. Paul Glasserman & Jeremy Staum, 2001. "Conditioning on One-Step Survival for Barrier Option Simulations," Operations Research, INFORMS, vol. 49(6), pages 923-937, December.
    3. Heston, Steven L, 1993. "A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options," The Review of Financial Studies, Society for Financial Studies, vol. 6(2), pages 327-343.
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    Cited by:

    1. A. Aimi & C. Guardasoni & L. Ortiz-Gracia & S. Sanfelici, 2023. "Fast Barrier Option Pricing by the COS BEM Method in Heston Model," Papers 2301.00648, arXiv.org, revised Jan 2023.
    2. Weilong Fu & Ali Hirsa, 2022. "Solving barrier options under stochastic volatility using deep learning," Papers 2207.00524, arXiv.org.
    3. Zhijian He & Xiaoqun Wang, 2021. "An Integrated Quasi-Monte Carlo Method for Handling High Dimensional Problems with Discontinuities in Financial Engineering," Computational Economics, Springer;Society for Computational Economics, vol. 57(2), pages 693-718, February.

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