Large and moderate deviations for importance sampling in the Heston model

Marc Geha (), Antoine Jacquier () and Žan Žurič ()
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Marc Geha: Princeton University
Antoine Jacquier: Imperial College London, and Alan Turing Institute
Žan Žurič: Imperial College London

Annals of Operations Research, 2024, vol. 336, issue 1, No 4, 47-92

Abstract: 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.

Keywords: Heston; Volatility; Importance sampling; Large deviations; Moderate deviations; 60F10; 65C05; 91G20 (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s10479-023-05424-0

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