Skip to main content
Log in

An explicit second-order numerical scheme for mean-field forward backward stochastic differential equations

  • Original Paper
  • Published:
Numerical Algorithms Aims and scope Submit manuscript

Abstract

In this paper, we propose an explicit second-order scheme for solving decoupled mean-field forward backward stochastic differential equations. Its stability is theoretically proved, and its error estimates are rigorously deduced, which show that the proposed scheme is of second-order accurate when the weak-order 2.0 Itô-Taylor scheme is used to solve mean-field stochastic differential equations. Some numerical experiments are presented to verify the theoretical results.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Ahdersson, D., Djehiche, B.: A maximum principle for SDEs of mean-field type. Appl. Math. Opt. 63, 341–356 (2011)

    Article  MathSciNet  Google Scholar 

  2. Bensoussan, A., Frehse, J., Yam, P.: Mean field games and mean field type control theory. Springer briefs in Mathematics (2013)

  3. Bossy, M., Talay, D.: A stochastic particle method for the McKean-Vlasov and the Burgers equation. Math. Comput. 66, 157–192 (1997)

    Article  MathSciNet  Google Scholar 

  4. Bouchard, B., Tan, X., Warin, X., Zou, Y.: Numerical approximation of BSDEs using local polynomial drivers and branching processes. Monte Carlo Methods Appl. 23, 241–263 (2017)

    Article  MathSciNet  Google Scholar 

  5. Bouchard, B., Possamaï, D., Tan, X., Zhou, C.: A unified approach to a priori estimates for supersolutions of BSDEs in general filtrations. Ann. Inst. Henri Poincaré Probab. Stat. 54, 154–172 (2018)

    Article  MathSciNet  Google Scholar 

  6. Buckdahn, R., Djehiche, B., Li, J., Peng, S.: Mean-field backward stochastic differential equations: a limit approach. Ann. Probab. 37, 1524–1565 (2009)

    Article  MathSciNet  Google Scholar 

  7. Buckdahn, R., Li, J., Peng, S.: Mean-field backward stochastic differential equations and related partial differential equations. Stochastic Pro Appl. 119, 3133–3154 (2009)

    Article  MathSciNet  Google Scholar 

  8. Carmona, R., Delarue, F.: Probabilistic analysis of mean-field games. SIAM J. Control Optim. 51, 2705–2734 (2012)

    Article  MathSciNet  Google Scholar 

  9. Fu, Y., Zhao, W., Zhou, T.: Efficient spectral sparse grid approximations for solving multidimensional forward backward SDEs. Discrete Contin. Dyn. Syst. Ser. B 22, 3439–3458 (2017)

    MathSciNet  MATH  Google Scholar 

  10. Gobet, E., Labart, C.: Error expansion for the discretization of backward stochastic differential equations. Stoch. Process Appl. 117, 803–829 (2007)

    Article  MathSciNet  Google Scholar 

  11. Guéant, O., Lasry, J., Lions, P.: Mean Field Games and Applications. Paris-Princeton Lectures on Mathematical Finance 2010, pp 205–266. Springer, Berlin (2011)

    Book  Google Scholar 

  12. Hafayed, M.: A mean-field necessary sufficient conditions for optimal singular stochastic control. Commun. Math. Stat. 1, 417–435 (2013)

    Article  MathSciNet  Google Scholar 

  13. Kloeden, P. E., Platen, E.: Numerical Solution of Stochastic Differential Equations. Springer, Berlin (1992)

    Book  Google Scholar 

  14. Kotelenez, P.: A class of quasilinear stochastic partial differential equations of McKean-Vlasov type with mass conservation. Probab. Theory Related Fields 102, 159–188 (1995)

    Article  MathSciNet  Google Scholar 

  15. Kharroubi, I., Langrené, N., Pham, H.: Discrete time approximation of fully nonlinear HJB equations via BSDEs with nonpositive jumps. Ann. Appl. Probab. 25, 2301–2338 (2015)

    Article  MathSciNet  Google Scholar 

  16. Lasry, J., Lions, P.: Mean field games. Jpn. J. Math. 2, 229–260 (2007)

    Article  MathSciNet  Google Scholar 

  17. Li, J.: Stochastic maximum principle in the mean-field controls. Automatica 48, 366–373 (2012)

    Article  MathSciNet  Google Scholar 

  18. Li, J., Min, H.: Controlled mean-field backward stochastic differential equations with jumps involving the value function. J. Syst. Sci. Comput. 29, 1–31 (2016)

    MathSciNet  MATH  Google Scholar 

  19. Mendoza, M. L., Aguilar, M. A., Valle, F. J.: A mean field approach that combines quantum mechanics and molecular dynamics simulation: the water molecule in liquid water. J. Mol. Struct. 426, 181–190 (1998)

    Article  Google Scholar 

  20. Ni, Y., Li, X., Zhang, J.: Mean-field stochastic linear-quadratic optimal control with Markov jump parameters. Systems Control Lett 93, 69–76 (2016)

    Article  MathSciNet  Google Scholar 

  21. Possamai, D., Tan, X., Zhou, C.: Stochastic control for a class of nonlinear kernels and applications. Ann. Probab. 46, 551–603 (2018)

    Article  MathSciNet  Google Scholar 

  22. Sun, Y., Yang, J., Zhao, W.: Itô-Taylor schemes for solving mean-field stochastic differential equations. Numer. Math. Theor. Meth. Appl. 10, 798–828 (2017)

    Article  Google Scholar 

  23. Sun, Y., Zhao, W.: New second-order schemes for forward backward stochastic differential equations. East Asian J. Appl. Math. 8, 399–421 (2018)

    Article  MathSciNet  Google Scholar 

  24. Sun, Y., Zhao, W., Zhou, T.: Explicit 𝜃-scheme for solving mean-field backward stochastic differential equations. SIAM J. Numer. Anal. 56, 2672–2697 (2018)

    Article  MathSciNet  Google Scholar 

  25. Tang, T., Zhao, W., Zhou, T.: Deferred correction methods for forward backward stochastic differential equations. Numer. Math. Theor. Meth. Appl. 10, 222–242 (2017)

    Article  MathSciNet  Google Scholar 

  26. Wang, B., Zhang, J.: Mean field games for large-population multi-agent systems with Markov jump parameters. SIAM J. Control Optim. 50, 2308–2334 (2012)

    Article  MathSciNet  Google Scholar 

  27. Wang, G., Zhang, C., Zhang, W.: Stochastic maximum principle for mean-field type optimal control under partial information. IEEE Trans. Autom. Control 59, 522–528 (2014)

    Article  MathSciNet  Google Scholar 

  28. Zhao, W., Chen, L., Peng, S.: A new kind of accurate numerical method for backward stochastic differential equations. SIAM J. Sci. Comput. 28, 1563–1581 (2006)

    Article  MathSciNet  Google Scholar 

  29. Zhao, W., Zhang, G., Ju, L.: A stable multistep scheme for solving backward stochastic differential equations. SIAM J. Numer. Anal. 48, 1369–1394 (2010)

    Article  MathSciNet  Google Scholar 

  30. Zhao, W., Li, Y., Zhang, G.: A generalized 𝜃-scheme for solving backward stochastic differential equations. Discrete Contin. Dyn. Syst. Ser. B 17, 1585–1603 (2012)

    Article  MathSciNet  Google Scholar 

  31. Zhao, W., Fu, Y., Zhou, T.: New kinds of high-order multistep schemes for coupled forward backward stochastic differential equations. SIAM J. Sci. Comput. 36, A1731–A1751 (2014)

    Article  MathSciNet  Google Scholar 

  32. Zhao, W., Zhou, T., Kong, T.: High order numerical schemes for second-order FBSDEs with applications to stochastic optimal control. Commun. Comput. Phys. 21, 808–834 (2017)

    Article  MathSciNet  Google Scholar 

Download references

Acknowledgments

The authors would like to thank the referees for their valuable comments and suggestions which helped to improve much of the quality of the paper.

Funding

This research is partially supported by the science challenge Project (No. TZ2018001), the NSF of China (under Grant Nos. 11571351, 11571206, 11831010, 11871068)

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Weidong Zhao.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sun, Y., Zhao, W. An explicit second-order numerical scheme for mean-field forward backward stochastic differential equations. Numer Algor 84, 253–283 (2020). https://doi.org/10.1007/s11075-019-00754-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11075-019-00754-2

Keywords

Mathematics Subject Classification (2010)

Navigation