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AIMS Mathematics, 2017, 2(3): 377-384. doi: 10.3934/Math.2017.3.377. Research article

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Approximation of solutions of multi-dimensional linear stochastic differential equations defined by weakly dependent random variables

Hiroshi Takahashi, Ken-ichi Yoshihara

1 Department of Mathematics, Tokyo Gakugei University, Koganei, Tokyo, 184-8501, Japan
2 Department of Mathematics, Yokohama National University, Hodogaya, Yokohama, 240-8501, Japan

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It is well-known that under suitable conditions there exists a unique solution of a ddimensional linear stochastic differential equation. The explicit expression of the solution, however, is not given in general. Hence, numerical methods to obtain approximate solutions are useful for such stochastic di erential equations. In this paper, we consider stochastic difference equations corresponding to linear stochastic differential equations. The difference equations are constructed by weakly dependent random variables, and this formulation is raised by the view points of time series. We show a convergence theorem on the stochastic difference equations.

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Keywords: Difference equation; weakly dependent random variables; Euler-Maruyama scheme; strong invariance principle; linear stochastic di erential equation

Citation: Hiroshi Takahashi, Ken-ichi Yoshihara. Approximation of solutions of multi-dimensional linear stochastic differential equations defined by weakly dependent random variables. AIMS Mathematics, 2017, 2(3): 377-384. doi: 10.3934/Math.2017.3.377

References:

1. P. E. Kloden and E. Platen, Numerical solution of stochastic differential equations, Springer-Verlag, Berlin Heidelberg, 1992.
2. W. Liu and Z. Lin, Strong approximation for a class of stationary processes, Stoch. Proc. Appl., 119 (2009), 249-280.
3. X. Mao, Stochastic differential equations and applications, second edition. Horwood Publishing Limited, Chichester, 2008.
4. H.Takahashi, S. Kanagawa and K. Yoshihara, Asymptotic behavior of solutions of some difference equations defined by weakly dependent random vectors, Stoch. Anal. Appl., 33 (2015), 740-755.
5. H.Takahashi, T. Saigo, S. Kanagawa and K. Yoshihara, Optimal portfolios based on weakly dependent data, Dyn. Syst. Differ. Equ. Appl., AIMS Proceedings, (2015), 1041-1049.
6. H.Takahashi, T. Saigo and K. Yoshihara, Approximation of optimal prices when basic data are weakly dependent, Dyn. Contin. Discrete Impuls. Syst. Ser. B, 23 (2016), 217-230.
7. K. Yoshihara, Asymptotic behavior of solutions of Black-Scholes type equations based on weakly dependent random variables, Yokohama Math. J., 58 (2012), 1-15.

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Copyright Info: 2017, Hiroshi Takahashi, et al., licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution Licese (http://creativecommons.org/licenses/by/4.0)

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