A fast method for pricing American options under the variance gamma model

Weilong Fu and Ali Hirsa

Papers from arXiv.org

Abstract: We investigate methods for pricing American options under the variance gamma model. The variance gamma process is a pure jump process which is constructed by replacing the calendar time by the gamma time in a Brownian motion with drift, which makes it a time-changed Brownian motion. In general, the finite difference method and the simulation method can be used for pricing under this model, but their speed is not satisfactory. So there is a need for fast but accurate approximation methods. In the case of Black-Merton-Scholes model, there are fast approximation methods, but they cannot be utilized for the variance gamma model. We develop a new fast method inspired by the quadratic approximation method, while reducing the error by making use of a machine learning technique on pre-calculated quantities. We compare the performance of our proposed method with those of the existing methods and show that this method is efficient and accurate for practical use.

Date: 2019-03
New Economics Papers: this item is included in nep-big and nep-cmp
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Citations: View citations in EconPapers (2)

Published in Journal of Computational Finance, 2021

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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:1903.07519

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