Strong convergence of explicit schemes for highly nonlinear stochastic differential equations with Markovian switching

Jingjun Zhao, Yulian Yi and Yang Xu

Applied Mathematics and Computation, 2021, vol. 398, issue C

Abstract: Two projected Euler type schemes are analyzed for stochastic differential equations with Markovian switching whose coefficients are super-linear. Under the polynomial growth condition and the monotone condition, we investigate the convergence in mean square sense of these numerical methods. Besides, we also discuss the convergence rates of these two schemes for highly nonlinear equations (including stochastic differential equations with and without Markovian switching) with small noise. Finally, some numerical experiments are given to verify our theoretical results.

Keywords: Stochastic differential equation; Markov process; Monotone condition; Mean square convergence; Small noise (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:398:y:2021:i:c:s0096300321000072

DOI: 10.1016/j.amc.2021.125959

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