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Frontiers of Mathematics in China

ISSN 1673-3452

ISSN 1673-3576(Online)

CN 11-5739/O1

Postal Subscription Code 80-964

2018 Impact Factor: 0.565

Front. Math. China    2015, Vol. 10 Issue (2) : 415-434    https://doi.org/10.1007/s11464-014-0366-6
RESEARCH ARTICLE
Euler-type schemes for weakly coupled forward-backward stochastic differential equations and optimal convergence analysis
Wei ZHANG,Weidong ZHAO()
School of Mathematics, Finance Institute, Shandong University, Jinan 250100, China
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Abstract

We introduce a new Euler-type scheme and its iterative algorithm for solving weakly coupled forward-backward stochastic differential equations (FBSDEs). Although the schemes share some common features with the ones proposed by C. Bender and J. Zhang [Ann. Appl. Probab., 2008, 18: 143–177], less computational work is needed for our method. For both our schemes and the ones proposed by Bender and Zhang, we rigorously obtain first-order error estimates, which improve the half-order error estimates of Bender and Zhang. Moreover, numerical tests are given to demonstrate the first-order accuracy of the schemes.

Keywords Weakly coupled forward-backward stochastic differential equations (FBSDEs)      time discretization      first-order      error estimate      Euler-type scheme     
Corresponding Author(s): Weidong ZHAO   
Issue Date: 12 February 2015
 Cite this article:   
Wei ZHANG,Weidong ZHAO. Euler-type schemes for weakly coupled forward-backward stochastic differential equations and optimal convergence analysis[J]. Front. Math. China, 2015, 10(2): 415-434.
 URL:  
https://academic.hep.com.cn/fmc/EN/10.1007/s11464-014-0366-6
https://academic.hep.com.cn/fmc/EN/Y2015/V10/I2/415
1 Bally V. Approximation scheme for solutions of BSDE. In: Backward Stochastic Differential Equations (Paris, 1995-1996), Pitman Res Notes Math, Ser 364. Harlow: Longman, 1997: 177-191
2 Bally V, Pages G. A quantization algorithm for solving multi-dimensional discrete-time optimal stopping problems. Bernoulli, 2003, 9: 1003-1049
https://doi.org/10.3150/bj/1072215199
3 Bender C, Zhang J. Time discretization and Markovian iteration for coupled FBSDEs. Ann Appl Probab, 2008, 18: 143-177
https://doi.org/10.1214/07-AAP448
4 Bouchard B, Touzi N. Discrete-time approximation and Monte-Carlo simulation of backward stochastic differential equations. Stochastic Process Appl, 2004, 111: 175-206
https://doi.org/10.1016/j.spa.2004.01.001
5 Crisan D, Manolarakis K. Second order discretization of backward S<?Pub Caret?>DEs. arXiv: 1012.5650
6 Cvitanic J, Zhang J. The steepest descent method for forward-backward SDEs. Electron J Probab, 2005, 10: 1468-1495
https://doi.org/10.1214/EJP.v10-295
7 Delarue F, Menozzi S. A forward-backward stochastic algorithm for quasi-linear PDEs. Ann Appl Probab, 2006, 16: 140-184
https://doi.org/10.1214/105051605000000674
8 Delarue F, Menozzi S. An interpolated stochastic algorithm for quasi-linear PDEs. Math Comp, 2008, 77: 125-158
https://doi.org/10.1090/S0025-5718-07-02008-X
9 Douglas J, Ma J, Protter P. Numerical methods for forward-backward stochastic differential equations. Ann Appl Probab, 1996, 6: 940-968
https://doi.org/10.1214/aoap/1034968235
10 Gianin E R. Risk measures via g-expectations. Insurance Math Econom, 2006, 39: 19-34
https://doi.org/10.1016/j.insmatheco.2006.01.002
11 Hamadene S, Lepeltier J P. Zero-sum stochastic differential games and backward equations. Systems Control Lett, 1995, 24: 259-263
https://doi.org/10.1016/0167-6911(94)00011-J
12 Karoui N EL, Peng S G, Quenez M C. Backward stochastic differential equations in finance. Math Finance, 1997, 7: 1-71
https://doi.org/10.1111/1467-9965.00022
13 Lemor J P, Gobet E, Warin X. A regression-based Monte Carlo method for backward stochastic differential equations. Ann Appl Probab, 2005, 15: 2172-2202
https://doi.org/10.1214/105051605000000412
14 Lemor J P, Gobet E, Warin X. Rate of convergence of an empirical regression method for solving generalized backward stochastic differential equations. Bernoulli, 2006, 12: 889-916
https://doi.org/10.3150/bj/1161614951
15 Li Y, Zhao W D. Lp-error estimates for numerical schemes for solving certain kinds of backward stochastic differential equations. Statist Probab Lett, 2010, 80: 1612-1617
https://doi.org/10.1016/j.spl.2010.06.015
16 Ma J, Protter P, Martin J S, Torres S. Numerical method for backward stochastic differential equations. Ann Appl Probab, 2002, 12: 302-316
https://doi.org/10.1214/aoap/1015961165
17 Ma J, Protter P, Yong J M. Solving forward-backward stochastic differential equations explicitly—a four step scheme. Probab Theory Related Fields, 1994, 98: 339-359
https://doi.org/10.1007/BF01192258
18 Ma J, Shen J, Zhao Y. On numerical approximations of forward-backward stochastic differential equations. SIAM J Numer Anal, 2008, 46: 2636-2661
https://doi.org/10.1137/06067393X
19 Ma J, Yong J M. Forward-Backward Stochastic Differential Equations and Their Applications. Lecture Notes in Mathematics, Vol 1702. Berlin: Springer, 1999
20 Milstein G N, Tretyakov M V. Numerical algorithms for forward-backward stochastic differential equations. SIAM J Sci Comput, 2006, 28: 561-582
https://doi.org/10.1137/040614426
21 Pardoux E, Peng S G. Adapted solution of a backward stochastic differential equation. Systems Control Lett, 1990, 14: 55-61
https://doi.org/10.1016/0167-6911(90)90082-6
22 Pardoux E, Tang S. Forward-backward stochastic differential equations and quasilinear parabolic PDEs. Probab Theory Related Fields, 1999, 114: 123-150
https://doi.org/10.1007/s004409970001
23 Peng S G. A general stochastic maximum principle for optimal control problems. SIAM J Control Optim, 1990, 28: 966-979
https://doi.org/10.1137/0328054
24 Peng S G. Probabilistic interpretation for systems of quasilinear parabolic partial differential equations. Stochastics and Stochastic Reports, 1991, 37: 61-74
https://doi.org/10.1080/17442509108833727
25 Peng S G. Backward SDE and related g-Expectation (Paris, 1995-1996). Pitman Res Notes Math, Ser 364. Harlow: Longman, 1997: 141-159
26 Peng S G. Nonlinear expectations, nonlinear evaluations and risk measures. In: Stochastic Methods in Finance. Lecture Notes in Mathematics, Vol 1856. 2004, 243-256
https://doi.org/10.1007/978-3-540-44644-6_4
27 Peng S G, Wu Z. Fully coupled forward-backward stochastic differential equations and applications to optimal control. SIAM J Control Optim, 1999, 37: 825-843
https://doi.org/10.1137/S0363012996313549
28 Zhang J. A numerical scheme for BSDEs. Ann Appl Probab, 2004, 14: 459-488
https://doi.org/10.1214/aoap/1075828058
29 Zhao W D, Chen L F, Peng S G. A new kind of accurate numerical method for backward stochastic differential equations. SIAM J Sci Comput, 2006, 28: 1563-1581
https://doi.org/10.1137/05063341X
30 Zhao W D, Fu Y, Zhou T. A new kind of high-order multi-step schemes for forward backward stochastic differential equations. arXiv: 1310.5307, revised
31 Zhao W D, Li Y, Ju L L. Error estimates of the Crank-Nicolson scheme for solving backward stochastic differential equations. Int J Numer Anal Model, 2013, 10: 876-898
32 Zhao W D, Li Y, Zhang G N. A generalized θ-scheme for solving backward stochastic differential equations. Discrete Contin Dyn Syst Ser B, 2012, 17: 1585-1603
https://doi.org/10.3934/dcdsb.2012.17.1585
33 Zhao W D, Wang J L, Peng S G. Error estimates of the θ-scheme for backward stochastic differential equations. Discrete Contin Dyn Syst Ser B, 2009, 12: 905-924
https://doi.org/10.3934/dcdsb.2009.12.905
34 Zhao W D, Zhang G N, Ju L L. A stable multistep scheme for solving backward stochastic differential equations. SIAM J Numer Anal, 2010, 48: 1369-1394
https://doi.org/10.1137/09076979X
35 Zhao W D, Zhang W, Ju L L. A numerical method and its error estimates for the decoupled forward-backward stochastic differential equations. Commun Comput Phys, 2014, 15: 618-646
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