Convergence of the Euler–Maruyama method for stochastic differential equations with Markovian switching

Chenggui Yuan and Xuerong Mao

Mathematics and Computers in Simulation (MATCOM), 2004, vol. 64, issue 2, 223-235

Abstract: Stochastic differential equations with Markovian switching (SDEwMSs), one of the important classes of hybrid systems, have been used to model many physical systems that are subject to frequent unpredictable structural changes. The research in this area has been both theoretical and applied. Most of SDEwMSs do not have explicit solutions so it is important to have numerical solutions. It is surprising that there are not any numerical methods established for SDEwMSs yet, although the numerical methods for stochastic differential equations (SDEs) have been well studied. The main aim of this paper is to develop a numerical scheme for SDEwMSs and estimate the error between the numerical and exact solutions. This is the first paper in this direction and the emphasis lies on the error analysis.

Keywords: Brownian motion; Euler–Maruyama method; Lipschitz condition; Markov chain generator (search for similar items in EconPapers)
Date: 2004
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Citations: View citations in EconPapers (11)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:64:y:2004:i:2:p:223-235

DOI: 10.1016/j.matcom.2003.09.001

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