Abstract
In this paper a family of fully implicit Milstein methods are introduced for solving stiff stochastic differential equations (SDEs). It is proved that the methods are convergent with strong order 1.0 for a class of SDEs. For a linear scalar test equation with multiplicative noise terms, mean-square and almost sure asymptotic stability of the methods are also investigated. We combine analytical and numerical techniques to get insights into the stability properties. The fully implicit methods are shown to be superior to those of the corresponding semi-implicit methods in term of stability property. Finally, numerical results are reported to illustrate the convergence and stability results.
Similar content being viewed by others
References
Ahmad, Sk.S., Parida, N.C., Raha, S.: The fully implicit stochastic-α method for stiff stochastic differential equations. J. Comput. Phys. 228, 8263–8282 (2009)
Alcock, J., Burrage, K.: A note on the balanced method. BIT Numer. Math. 46(4), 689–710 (2006)
Arnold, L.: Stochastic Differential Equation: Theory and Application. Wiley, New York (1974)
Bodo, B.A., Thompson, M.E., Unny, T.E.: A review on stochastic differential equations for application in hydrology. Stoch. Hydrol. Hydraul. 1, 81–100 (1987)
Buckwar, E., Bokor, R.H., Winkler, R.: Asymptotic mean-square stability of two-step methods for stochastic ordinary differential equations. BIT Numer. Math. 46, 261–282 (2006)
Buckwar, E., Kelly, C.: Towards a systematic linear stability analysis of numerical methods for systems of stochastic differential equations. SIAM J. Numer. Anal. 48(1), 298–321 (2010)
Buckwar, E., Sickenberger, T.: A comparative linear mean-square stability analysis of Maruyama and Milstein-type methods. Math. Comput. Simul. 81, 1110–1127 (2011)
Burrage, K., Burrage, P.M., Tian, T.: Numerical methods for strong solutions of stochastic differential equations: an overview. In: Proceedings: Mathematical, Physical and Engineering, Royal Society of London, vol. 460, pp. 373–402 (2004)
Burrage, K., Tian, T.: The composite Euler method for stiff stochastic differential equations. J. Comput. Appl. Math. 131, 407–426 (2000)
Chalmers, G., Higham, D.J.: Asymptotic stability of a jump-diffusion equation and its numerical approximation. SIAM J. Sci. Comput. 31, 1141–1155 (2008)
Gard, T.C.: Introduction to Stochastic Differential Equations. Dekker, New York (1988)
Hairer, E., Wanner, G.: Solving Ordinary Differential Equations II: Stiff and Differential-Algebraic Problems, 2nd edn. Springer, Berlin (1996)
Halley, W., Malham, S., Wiese, A.: Positive and implicit stochastic volatility simulation. arXiv:0802.4411v2 (2008)
Higham, D.J.: Mean-square and asymptotic stability of the stochastic theta method. SIAM J. Numer. Anal. 38, 753–769 (2000)
Kahl, C., Schurz, H.: Balanced Milstein methods for ordinary SDEs. Monte Carlo Methods Appl. 12(2), 143–170 (2006)
Kloeden, P.E., Platen, E.: Numerical Solution of Stochastic Differential Equations. Springer, Berlin (1992)
Kloeden, P.E., Platen, E., Schurz, H.: The numerical solution of nonlinear stochastic dynamical systems: A brief introduction. Int. J. Bifurc. Chaos 1, 277–286 (1991)
Mao, X.: Stochastic Differential Equations and Applications. Horwood, New York (1997)
Milstein, G.N., Platen, E., Schurz, H.: Balanced implicit methods for stiff stochastic systems. SIAM J. Numer. Anal. 35, 1010–1019 (1998)
Milstein, G.N., Repin, Yu.M., Tretyakov, M.V.: Numerical methods for stochastic systems preserving symplectic structure. SIAM J. Numer. Anal. 40(4), 1583–1604 (2002)
Milstein, G.N., Tretyakov, M.V.: Stochastic Numerics for Mathematical Physics. Springer, Berlin (2004)
Omar, M.A., Aboul-Hassan, A., Rabia, S.I.: The composite Milstein methods for the numerical solution of Stratonovich stochastic differential equations. Appl. Math. Comput. 215, 727–745 (2009)
Rodkina, A., Schurz, H.: Almost sure asymptotic stability of drift-implicit methods for bilinear ordinary stochastic differential equations in ℝ1. J. Comput. Appl. Math. 180, 13–31 (2005)
Saito, Y., Mitsui, T.: Stability analysis of numerical schemes for stochastic differential equations. SIAM J. Numer. Anal. 33, 2254–2267 (1996)
Tian, T.H., Burrage, K.: Implicit Taylor methods for stiff stochastic differential equations. Appl. Numer. Math. 38, 167–185 (2001)
Tian, T.H., Burrage, K.: Two-stage stochastic Runge-Kutta methods for stochastic differential equations. BIT 42, 625–643 (2002)
van Kampen, N.G.: Stochastic Processes in Physics and Chemistry. Elsevier, Amsterdam (1992)
Wang, X., Gan, S.: Compensated stochastic theta methods for stochastic differential equations with jumps. Appl. Numer. Math. 60, 877–887 (2010)
Wu, F., Mao, X., Szpruch, L.: Almost sure exponential stability of numerical solutions for stochastic delay differential equations. Numer. Math. 115(4), 681–697 (2010)
Acknowledgements
This work was supported by NSF of China (No. 11171352), Hunan Provincial Innovation Foundation For Postgraduate (No. CX2010B118), Singapore AcRF RG 59/08 (M52110092) and Singapore NRF 2007 IDM-IDM002-010. The first author would like to express his deep gratitude to Prof. P.E. Kloeden and Dr. A. Jentzen for their kind help and useful discussions during his stay in Goethe University of Frankfurt am Main.
Author information
Authors and Affiliations
Corresponding author
Additional information
Communicated by Anders Szepessy.
Rights and permissions
About this article
Cite this article
Wang, X., Gan, S. & Wang, D. A family of fully implicit Milstein methods for stiff stochastic differential equations with multiplicative noise. Bit Numer Math 52, 741–772 (2012). https://doi.org/10.1007/s10543-012-0370-8
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10543-012-0370-8
Keywords
- Fully implicit Milstein method
- Stiff stochastic differential equation
- Strong convergence
- Mean-square stability
- Almost sure asymptotic stability