A high order weak approximation for jump-diffusions using Malliavin calculus and operator splitting

Akiyama Naho () and Yamada Toshihiro ()
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Akiyama Naho: Hitotsubashi University, Tokyo, Japan
Yamada Toshihiro: Hitotsubashi University; and Japan Science and Technology Agency (JST), Tokyo, Japan

Monte Carlo Methods and Applications, 2022, vol. 28, issue 2, 97-110

Abstract: The paper introduces a novel high order discretization scheme for expectation of jump-diffusion processes by using a Malliavin calculus approach and an operator splitting method. The test function of the target expectation is assumed to be only Lipschitz continuous in order to apply the method to financial problems. Then Kusuoka’s estimate is employed to justify the proposed discretization scheme. The algorithm with a numerical example is shown for implementation.

Keywords: Weak approximation; stochastic differential equation; jump-diffusion; Malliavin calculus; operator splitting (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1515/mcma-2022-2109

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