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Revisiting the numerical solution of stochastic differential equations

Author

Listed:
  • Stan Hurn
  • Kenneth A. Lindsay
  • Lina Xu

Abstract

Purpose - The purpose of this paper is to revisit the numerical solutions of stochastic differential equations (SDEs). An important drawback when integrating SDEs numerically is the number of steps required to attain acceptable accuracy of convergence to the true solution. Design/methodology/approach - This paper develops a bias reducing method based loosely on extrapolation. Findings - The method is seen to perform acceptably well and for realistic steps sizes provides improved accuracy at no significant additional computational cost. In addition, the optimal step size of the bias reduction methods is shown to be consistent with theoretical analysis. Originality/value - Overall, there is evidence to suggest that the proposed method is a viable, easy to implement competitor for other commonly used numerical schemes.

Suggested Citation

  • Stan Hurn & Kenneth A. Lindsay & Lina Xu, 2019. "Revisiting the numerical solution of stochastic differential equations," China Finance Review International, Emerald Group Publishing Limited, vol. 9(3), pages 312-323, August.
  • Handle: RePEc:eme:cfripp:cfri-12-2018-0155
    DOI: 10.1108/CFRI-12-2018-0155
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    More about this item

    Keywords

    Monte Carlo simulation; Stochastic differential equations; C22; C52;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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