Open Access Journals

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

Export file:

Format

RIS(for EndNote,Reference Manager,ProCite)
BibTex
Text

Content

Citation Only
Citation and Abstract

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

Received: , Accepted: , Published:

Abstract Full Text(HTML) Figure/Table

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.

Figure/Table

Supplementary

Article Metrics

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.

show all references

Reader Comments

your name: * your email: *

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)

Download full text in PDF

Associated material

Metrics