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Neural variance reduction for stochastic differential equations

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  • P. D. Hinds
  • M. V. Tretyakov

Abstract

Variance reduction techniques are of crucial importance for the efficiency of Monte Carlo simulations in finance applications. We propose the use of neural SDEs, with control variates parameterized by neural networks, in order to learn approximately optimal control variates and hence reduce variance as trajectories of the SDEs are being simulated. We consider SDEs driven by Brownian motion and, more generally, by L\'{e}vy processes including those with infinite activity. For the latter case, we prove optimality conditions for the variance reduction. Several numerical examples from option pricing are presented.

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  • P. D. Hinds & M. V. Tretyakov, 2022. "Neural variance reduction for stochastic differential equations," Papers 2209.12885, arXiv.org, revised May 2023.
    • Handle: RePEc:arx:papers:2209.12885
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    1. Shiraya, Kenichiro & Takahashi, Akihiko, 2017. "A general control variate method for multi-dimensional SDEs: An application to multi-asset options under local stochastic volatility with jumps models in finance," European Journal of Operational Research, Elsevier, vol. 258(1), pages 358-371.
    2. Haozhe Su & M. V. Tretyakov & David P. Newton, 2021. "Deep learning of transition probability densities for stochastic asset models with applications in option pricing," Papers 2105.10467, arXiv.org, revised Jul 2023.
    3. M V Tretyakov, 2013. "Introductory Course on Financial Mathematics," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number p889, February.
    4. Merton, Robert C., 1976. "Option pricing when underlying stock returns are discontinuous," Journal of Financial Economics, Elsevier, vol. 3(1-2), pages 125-144.
    5. Shiraya, Kenichiro & Uenishi, Hiroki & Yamazaki, Akira, 2020. "A general control variate method for Lévy models in finance," European Journal of Operational Research, Elsevier, vol. 284(3), pages 1190-1200.
    6. 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.
    7. Dingeç, Kemal Dinçer & Hörmann, Wolfgang, 2012. "A general control variate method for option pricing under Lévy processes," European Journal of Operational Research, Elsevier, vol. 221(2), pages 368-377.
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