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Splitting Methods for Fokker-Planck Equations Related to Jump-Diffusion Processes

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Novel Methods in Computational Finance

Part of the book series: Mathematics in Industry ((TECMI,volume 25))

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Abstract

A splitting implicit-explicit (SIMEX) scheme for solving a partial integro-differential Fokker-Planck equation related to a jump-diffusion process is investigated. This scheme combines the method of Chang-Cooper for spatial discretization with the Strang-Marchuk splitting and first- and second-order time discretization methods. It is proven that the SIMEX scheme is second-order accurate, positive preserving, and conservative. Results of numerical experiments that validate the theoretical results are presented. (This chapter is a summary of the paper Gaviraghi et al. (Appl Math Comput, 2017); all theoretical statements in this summary are proved in that reference.)

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References

  1. Annunziato, M., Borzì, A.: A Fokker-Planck control framework for multidimensional stochastic processes. J. Comput. Appl. Math. 237, 487–507 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  2. Applebaum, D.: Lévy Processes and Stochastic Calculus. Cambridge University Press, Cambridge (2004)

    Book  MATH  Google Scholar 

  3. Briani, M., Natalini, R.: Asymptotic high-order schemes for integro-differential problems arising in markets with jumps. Commun. Math. Sci. 4, 81–96 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  4. Chang, J.S., Cooper, G.: A practical difference scheme for Fokker-Planck equations. J. Comput. Phys. 6, 1–16 (1970)

    Article  MATH  Google Scholar 

  5. Cont, R., Tankov, P.: Financial Modeling with Jump Processes. Chapman and Hall, London (2004)

    MATH  Google Scholar 

  6. Cont, R., Voltchkova, E.: Integro-differential equations for option prices in exponential Lévy models. Finance Stochast. 9, 299–325 (2005)

    Article  MATH  Google Scholar 

  7. Dahlquist, G., Björck, A.: Numerical Methods in Scientific Computing, vol. 1. Society for Industrial and Applied Mathematics, Philadelphia (2008)

    Book  MATH  Google Scholar 

  8. Gardiner, C.: Stochastic Methods: A Handbook for the Natural and Social Sciences. Springer, Berlin (2009)

    MATH  Google Scholar 

  9. Garroni, M.G., Menaldi, J.L.: Green Functions for Second-Order Parabolic Integro-Differential Problems. Longman, Harlow (1992)

    MATH  Google Scholar 

  10. Gaviraghi, B., Annunziato, M., Borzì, A.: Analysis of splitting methods for solving a partial-integro differential Fokker-Planck equation. Appl. Math. Comput. 294, 1–17 (2017)

    MathSciNet  Google Scholar 

  11. Geiser, J.: Decomposition Methods for Differential Equations: Theory and Applications. Chapman and Hall, London (2009)

    Book  MATH  Google Scholar 

  12. Hundsdorfer, W., Verwer, J.G.: Numerical Solutions of Time-Dependent Advection-Diffusion-Reaction Equations. Springer, Berlin (2010)

    MATH  Google Scholar 

  13. Kloeden, P.E., Platen, E.: Numerical Solutions of Stochastic Differential Equations. Springer, Berlin (1999)

    MATH  Google Scholar 

  14. Marchuk, G.I.: Methods of Numerical Mathematics. Springer, New York (1981)

    Google Scholar 

  15. Mohammadi, M., Borzì, A.: Analysis of the Chang-Cooper discretization scheme for a class of Fokker-Planck equations. J. Numer. Math. 23, 271–288 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  16. Pascucci, A.: PDE and Martingale Methods in Option Pricing. Springer, New York (2011)

    Book  MATH  Google Scholar 

  17. Paul, W., Baschnagel, J.: Stochastic Processes, from Physics to Finance. Springer, New York (2010)

    MATH  Google Scholar 

  18. Priola, E., Zabczyk, J.: Densities for Ornstein-Uhlenbeck processes with jumps. Bull. Lond. Math. Soc. 41, 41–50 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  19. Risken, R.: The Fokker-Planck Equation: Methods of Solution and Applications. Springer, New York (1996)

    Book  MATH  Google Scholar 

  20. Strang, G.: On the construction and comparison of difference schemes. SIAM J. Numer. Anal. 5, 506–517 (1968)

    Article  MathSciNet  MATH  Google Scholar 

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Correspondence to Alfio Borzì .

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Gaviraghi, B., Annunziato, M., Borzì, A. (2017). Splitting Methods for Fokker-Planck Equations Related to Jump-Diffusion Processes. In: Ehrhardt, M., Günther, M., ter Maten, E. (eds) Novel Methods in Computational Finance. Mathematics in Industry(), vol 25. Springer, Cham. https://doi.org/10.1007/978-3-319-61282-9_22

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