Pricing of geometric Asian options in the Volterra-Heston model

Geometric Asian options are a type of option where the payoff depends on the geometric mean of the underlying asset over a certain period of time. This paper is concerned with the pricing of such options for the class of Volterra-Heston models, covering the rough Heston model. We are able to derive semi-closed formulas for the prices of geometric Asian options with fixed and floating strikes for this class of stochastic volatility models. These formulas require the explicit calculation of the conditional joint Fourier transform of the logarithm of the stock price and the logarithm of the geometric mean of the stock price over time. Linking our problem to the theory of affine Volterra processes, we find a representation of this Fourier transform as a suitably constructed stochastic exponential, which depends on the solution of a Riccati-Volterra equation. Finally, we provide a numerical study for our results in the rough Heston model.

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Publication Details

Journal
Review of Derivatives Research
Published
2025-03-09
DOI
https://doi.org/10.1007/s11147-025-09211-w
Citations
1
Primary Topic
Stochastic processes and financial applications
Type
article
Field-Weighted Citation Impact
2.21

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article

Pricing of geometric Asian options in the Volterra-Heston model

Sascha Desmettre, Florian Aichinger
1 citations
Review of Derivatives Research
Stochastic processes and financial applications
2.21
article

Pricing of geometric Asian options in the Volterra-Heston model

Sascha Desmettre, Florian Aichinger
article en
1 citations

Abstract

Geometric Asian options are a type of option where the payoff depends on the geometric mean of the underlying asset over a certain period of time. This paper is concerned with the pricing of such options for the class of Volterra-Heston models, covering the rough Heston model. We are able to derive semi-closed formulas for the prices of geometric Asian options with fixed and floating strikes for this class of stochastic volatility models. These formulas require the explicit calculation of the conditional joint Fourier transform of the logarithm of the stock price and the logarithm of the geometric mean of the stock price over time. Linking our problem to the theory of affine Volterra processes, we find a representation of this Fourier transform as a suitably constructed stochastic exponential, which depends on the solution of a Riccati-Volterra equation. Finally, we provide a numerical study for our results in the rough Heston model.

Review of Derivatives ResearchVol. 28(1)
Johannes Kepler University of Linz (AT), Johann Radon Institute for Computational and Applied Mathematics (AT)
Austrian Science Fund
Openalex Percentile: Top 17%
Stochastic processes and financial applications
2.21
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