Approximation of Euler–Maruyama for one-dimensional stochastic differential equations involving the maximum process

Hiderah Kamal ()
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Hiderah Kamal: Department of Mathematics, Faculty of Science, University of Aden, Aden, Yemen

Monte Carlo Methods and Applications, 2020, vol. 26, issue 1, 33-47

Abstract: The aim of this paper is to show the approximation of Euler–Maruyama Xtn{X_{t}^{n}} for one-dimensional stochastic differential equations involving the maximum process. In addition to that it proves the strong convergence of the Euler–Maruyama whose both drift and diffusion coefficients are Lipschitz. After that, it generalizes to the non-Lipschitz case.

Keywords: Euler–Maruyama approximation; strong convergence; stochastic differential equations; maximum process (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1515/mcma-2020-2057

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