2016, 21(9): 3115-3162. doi: 10.3934/dcdsb.2016090

Taylor schemes for rough differential equations and fractional diffusions

1. 

Department of Mathematics, The University of Kansas, Lawrence, Kansas, 66045, United States, United States, United States

Received  October 2015 Revised  March 2016 Published  October 2016

In this paper, we study two variations of the time discrete Taylor schemes for rough differential equations and for stochastic differential equations driven by fractional Brownian motions. One is the incomplete Taylor scheme which excludes some terms of an Taylor scheme in its recursive computation so as to reduce the computation time. The other one is to add some deterministic terms to an incomplete Taylor scheme to improve the mean rate of convergence. Almost sure rate of convergence and $L_p$-rate of convergence are obtained for the incomplete Taylor schemes. Almost sure rate is expressed in terms of the Hölder exponents of the driving signals and the $L_p$-rate is expressed by the Hurst parameters. Both the almost sure and the $L_{p}$-convergence rates can be computed explicitly in terms of the parameters and the number of terms included in the incomplete scheme. In this way we can design the best incomplete schemes for the almost sure or the $L_p$-convergence. As in the smooth case, general Taylor schemes are always complicated to deal with. The incomplete Taylor scheme is even more sophisticated to analyze. A new feature of our approach is the explicit expression of the error functions which will be easier to study. Estimates for multiple integrals and formulas for the iterated vector fields are obtained to analyze the error functions and then to obtain the rates of convergence.
Citation: Yaozhong Hu, Yanghui Liu, David Nualart. Taylor schemes for rough differential equations and fractional diffusions. Discrete & Continuous Dynamical Systems - B, 2016, 21 (9) : 3115-3162. doi: 10.3934/dcdsb.2016090
References:
[1]

F. Baudoin and X. Zhang, Taylor expansion for the solution of a stochastic differential equation driven by fractional Brownian motions,, Electron. J. Probab., 17 (2012), 1. doi: 10.1214/EJP.v17-2136.

[2]

Q. Feng and X. Zhang, Taylor expansions and Castell estimates for solutions of stochastic differential equations driven by rough paths, preprint,, , ().

[3]

P. K. Friz and N. Victoir, Multidimentional Stochastic Processes as Rough Paths, Theory and Applications,, vol. 120 of Cambridge studies in advanced mathematics, (2010). doi: 10.1017/CBO9780511845079.

[4]

M. Gradinaru and I. Nourdin, Milstein's type schemes for fractional SDEs,, Ann. Inst. Henri Poincaré Probab. Stat., 45 (2009), 1085. doi: 10.1214/08-AIHP196.

[5]

Y. Hu, Strong and weak order of time discretization schemes of stochastic differential equations,, Séminaire de Probabilités XXX, 1626 (1996), 218. doi: 10.1007/BFb0094650.

[6]

Y. Hu, Multiple integrals and expansion of solutions of differential equations driven by rough paths and by fractional Brownian motions,, Stochastics, 85 (2013), 859. doi: 10.1080/17442508.2012.673615.

[7]

Y. Hu, Y. Liu and D. Nualart, Rate of convergence and asymptotic error distribution of Euler approximation schemes for fractional diffusions,, Ann. Appl. Probab., 26 (2016), 1147. doi: 10.1214/15-AAP1114.

[8]

Y. Hu and B. Øksendal, Fractional white noise calculus and applications to finance,, Infin. Dimens. Anal. Quantum Probab. Relat. Top., 6 (2003), 1. doi: 10.1142/S0219025703001110.

[9]

S. Janson, Gaussian Hilbert Spaces,, Cambridge University Press, (1997). doi: 10.1017/CBO9780511526169.

[10]

P. E. Kloeden and E. Platen, Numerical Solution of Stochastic Differential Equations,, Springer, (1992). doi: 10.1007/978-3-662-12616-5.

[11]

T. Lyons, Differential equations driven by rough signals. I. An extension of an inequality of L. C. Young,, Math. Res. Lett., 1 (1994), 451. doi: 10.4310/MRL.1994.v1.n4.a5.

[12]

T. Lyons, Differential equations driven by rough signals,, Rev. Mat. Iberoamericana, 14 (1998), 215. doi: 10.4171/RMI/240.

[13]

Y. Mishura, Stochastic Calculus for Fractional Brownian Motion and Related Processes,, Springer-Verlag, (2008). doi: 10.1007/978-3-540-75873-0.

[14]

A. Neuenkirch and I. Nourdin, Exact rate of convergence of some approximation schemes associated to SDEs driven by a fractional Brownian motion,, J. Theoret. Probab., 20 (2007), 871. doi: 10.1007/s10959-007-0083-0.

[15]

D. Nualart and A. Rascanu, Differential equations driven by fractional Brownian motion,, Collect. Math., 53 (2002), 55.

[16]

C. Reutenauer, Free Lie Algebra,, vol. 7 of London Mathematical Society Monographs, (1993).

[17]

M. Zähle, Integration with respect to fractal functions and stochastic calculus. I.,, Probab. Theory Related Fields, 111 (1998), 333. doi: 10.1007/s004400050171.

show all references

References:
[1]

F. Baudoin and X. Zhang, Taylor expansion for the solution of a stochastic differential equation driven by fractional Brownian motions,, Electron. J. Probab., 17 (2012), 1. doi: 10.1214/EJP.v17-2136.

[2]

Q. Feng and X. Zhang, Taylor expansions and Castell estimates for solutions of stochastic differential equations driven by rough paths, preprint,, , ().

[3]

P. K. Friz and N. Victoir, Multidimentional Stochastic Processes as Rough Paths, Theory and Applications,, vol. 120 of Cambridge studies in advanced mathematics, (2010). doi: 10.1017/CBO9780511845079.

[4]

M. Gradinaru and I. Nourdin, Milstein's type schemes for fractional SDEs,, Ann. Inst. Henri Poincaré Probab. Stat., 45 (2009), 1085. doi: 10.1214/08-AIHP196.

[5]

Y. Hu, Strong and weak order of time discretization schemes of stochastic differential equations,, Séminaire de Probabilités XXX, 1626 (1996), 218. doi: 10.1007/BFb0094650.

[6]

Y. Hu, Multiple integrals and expansion of solutions of differential equations driven by rough paths and by fractional Brownian motions,, Stochastics, 85 (2013), 859. doi: 10.1080/17442508.2012.673615.

[7]

Y. Hu, Y. Liu and D. Nualart, Rate of convergence and asymptotic error distribution of Euler approximation schemes for fractional diffusions,, Ann. Appl. Probab., 26 (2016), 1147. doi: 10.1214/15-AAP1114.

[8]

Y. Hu and B. Øksendal, Fractional white noise calculus and applications to finance,, Infin. Dimens. Anal. Quantum Probab. Relat. Top., 6 (2003), 1. doi: 10.1142/S0219025703001110.

[9]

S. Janson, Gaussian Hilbert Spaces,, Cambridge University Press, (1997). doi: 10.1017/CBO9780511526169.

[10]

P. E. Kloeden and E. Platen, Numerical Solution of Stochastic Differential Equations,, Springer, (1992). doi: 10.1007/978-3-662-12616-5.

[11]

T. Lyons, Differential equations driven by rough signals. I. An extension of an inequality of L. C. Young,, Math. Res. Lett., 1 (1994), 451. doi: 10.4310/MRL.1994.v1.n4.a5.

[12]

T. Lyons, Differential equations driven by rough signals,, Rev. Mat. Iberoamericana, 14 (1998), 215. doi: 10.4171/RMI/240.

[13]

Y. Mishura, Stochastic Calculus for Fractional Brownian Motion and Related Processes,, Springer-Verlag, (2008). doi: 10.1007/978-3-540-75873-0.

[14]

A. Neuenkirch and I. Nourdin, Exact rate of convergence of some approximation schemes associated to SDEs driven by a fractional Brownian motion,, J. Theoret. Probab., 20 (2007), 871. doi: 10.1007/s10959-007-0083-0.

[15]

D. Nualart and A. Rascanu, Differential equations driven by fractional Brownian motion,, Collect. Math., 53 (2002), 55.

[16]

C. Reutenauer, Free Lie Algebra,, vol. 7 of London Mathematical Society Monographs, (1993).

[17]

M. Zähle, Integration with respect to fractal functions and stochastic calculus. I.,, Probab. Theory Related Fields, 111 (1998), 333. doi: 10.1007/s004400050171.

[1]

Ahmed Boudaoui, Tomás Caraballo, Abdelghani Ouahab. Stochastic differential equations with non-instantaneous impulses driven by a fractional Brownian motion. Discrete & Continuous Dynamical Systems - B, 2017, 22 (7) : 2521-2541. doi: 10.3934/dcdsb.2017084

[2]

María J. Garrido–Atienza, Kening Lu, Björn Schmalfuss. Random dynamical systems for stochastic partial differential equations driven by a fractional Brownian motion. Discrete & Continuous Dynamical Systems - B, 2010, 14 (2) : 473-493. doi: 10.3934/dcdsb.2010.14.473

[3]

Xinfu Chen, Bei Hu, Jin Liang, Yajing Zhang. Convergence rate of free boundary of numerical scheme for American option. Discrete & Continuous Dynamical Systems - B, 2016, 21 (5) : 1435-1444. doi: 10.3934/dcdsb.2016004

[4]

Wen Li, Song Wang, Volker Rehbock. A 2nd-order one-point numerical integration scheme for fractional ordinary differential equations. Numerical Algebra, Control & Optimization, 2017, 7 (3) : 273-287. doi: 10.3934/naco.2017018

[5]

S. Kanagawa, K. Inoue, A. Arimoto, Y. Saisho. Mean square approximation of multi dimensional reflecting fractional Brownian motion via penalty method. Conference Publications, 2005, 2005 (Special) : 463-475. doi: 10.3934/proc.2005.2005.463

[6]

Caifang Wang, Tie Zhou. The order of convergence for Landweber Scheme with $\alpha,\beta$-rule. Inverse Problems & Imaging, 2012, 6 (1) : 133-146. doi: 10.3934/ipi.2012.6.133

[7]

Roberto Garrappa, Eleonora Messina, Antonia Vecchio. Effect of perturbation in the numerical solution of fractional differential equations. Discrete & Continuous Dynamical Systems - B, 2017, 22 (11) : 1-16. doi: 10.3934/dcdsb.2017188

[8]

Joseph A. Connolly, Neville J. Ford. Comparison of numerical methods for fractional differential equations. Communications on Pure & Applied Analysis, 2006, 5 (2) : 289-307. doi: 10.3934/cpaa.2006.5.289

[9]

Yong Ren, Xuejuan Jia, Lanying Hu. Exponential stability of solutions to impulsive stochastic differential equations driven by $G$-Brownian motion. Discrete & Continuous Dynamical Systems - B, 2015, 20 (7) : 2157-2169. doi: 10.3934/dcdsb.2015.20.2157

[10]

Shaokuan Chen, Shanjian Tang. Semi-linear backward stochastic integral partial differential equations driven by a Brownian motion and a Poisson point process. Mathematical Control & Related Fields, 2015, 5 (3) : 401-434. doi: 10.3934/mcrf.2015.5.401

[11]

Bahareh Akhtari, Esmail Babolian, Andreas Neuenkirch. An Euler scheme for stochastic delay differential equations on unbounded domains: Pathwise convergence. Discrete & Continuous Dynamical Systems - B, 2015, 20 (1) : 23-38. doi: 10.3934/dcdsb.2015.20.23

[12]

Weidong Zhao, Yang Li, Guannan Zhang. A generalized $\theta$-scheme for solving backward stochastic differential equations. Discrete & Continuous Dynamical Systems - B, 2012, 17 (5) : 1585-1603. doi: 10.3934/dcdsb.2012.17.1585

[13]

Yong Xu, Rong Guo, Di Liu, Huiqing Zhang, Jinqiao Duan. Stochastic averaging principle for dynamical systems with fractional Brownian motion. Discrete & Continuous Dynamical Systems - B, 2014, 19 (4) : 1197-1212. doi: 10.3934/dcdsb.2014.19.1197

[14]

Yong Xu, Bin Pei, Rong Guo. Stochastic averaging for slow-fast dynamical systems with fractional Brownian motion. Discrete & Continuous Dynamical Systems - B, 2015, 20 (7) : 2257-2267. doi: 10.3934/dcdsb.2015.20.2257

[15]

Guolian Wang, Boling Guo. Stochastic Korteweg-de Vries equation driven by fractional Brownian motion. Discrete & Continuous Dynamical Systems - A, 2015, 35 (11) : 5255-5272. doi: 10.3934/dcds.2015.35.5255

[16]

Tyrone E. Duncan. Some linear-quadratic stochastic differential games for equations in Hilbert spaces with fractional Brownian motions. Discrete & Continuous Dynamical Systems - A, 2015, 35 (11) : 5435-5445. doi: 10.3934/dcds.2015.35.5435

[17]

Yanzhao Cao, Anping Liu, Zhimin Zhang. Special section on differential equations: Theory, application, and numerical approximation. Discrete & Continuous Dynamical Systems - B, 2015, 20 (5) : i-ii. doi: 10.3934/dcdsb.2015.20.5i

[18]

Defei Zhang, Ping He. Functional solution about stochastic differential equation driven by $G$-Brownian motion. Discrete & Continuous Dynamical Systems - B, 2015, 20 (1) : 281-293. doi: 10.3934/dcdsb.2015.20.281

[19]

Tong Li, Hui Yin. Convergence rate to strong boundary layer solutions for generalized BBM-Burgers equations with non-convex flux. Communications on Pure & Applied Analysis, 2014, 13 (2) : 835-858. doi: 10.3934/cpaa.2014.13.835

[20]

Azmy S. Ackleh, Mark L. Delcambre, Karyn L. Sutton, Don G. Ennis. A structured model for the spread of Mycobacterium marinum: Foundations for a numerical approximation scheme. Mathematical Biosciences & Engineering, 2014, 11 (4) : 679-721. doi: 10.3934/mbe.2014.11.679

2016 Impact Factor: 0.994

Metrics

  • PDF downloads (0)
  • HTML views (0)
  • Cited by (0)

Other articles
by authors

[Back to Top]