Approximation of stochastic differential equations driven by subfractional Brownian motion at discrete time observation

Guangjun Shen, Zheng Tang and Jun Wang

Communications in Statistics - Theory and Methods, 2023, vol. 52, issue 1, 1-18

Abstract: In this paper, we consider discrete time approximations for stochastic differential equations with the form: Xt=X0+∫0tf(Xs)dhs+∫0tg(Xs)dYsH, t>0, where h:R+→R is a continuous function with locally bounded variation, f,g:R→R are measurable functions, and the integral with respect to YtH=∫0tσsdSsH is the pathwise Riemann-Stieltjes integral, SH is a subfractional Brownian motion with H∈(12,1), σ is a deterministic (possibly discontinuous) function.

Date: 2023
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DOI: 10.1080/03610926.2021.1901924

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