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Large and moderate deviations for importance sampling in the Heston model

Author

Listed:
  • Marc Geha

    (Princeton University)

  • Antoine Jacquier

    (Imperial College London, and Alan Turing Institute)

  • Žan Žurič

    (Imperial College London)

Abstract

We provide a detailed importance sampling analysis for variance reduction in stochastic volatility models. The optimal change of measure is obtained using a variety of results from large and moderate deviations: small-time, large-time, small-noise. Specialising the results to the Heston model, we derive many closed-form solutions, making the whole approach easy to implement. We support our theoretical results with a detailed numerical analysis of the variance reduction gains.

Suggested Citation

  • Marc Geha & Antoine Jacquier & Žan Žurič, 2024. "Large and moderate deviations for importance sampling in the Heston model," Annals of Operations Research, Springer, vol. 336(1), pages 47-92, May.
    • Handle: RePEc:spr:annopr:v:336:y:2024:i:1:d:10.1007_s10479-023-05424-0
    DOI: 10.1007/s10479-023-05424-0
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