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Approximation of stochastic equations driven by predictable processes
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  • Published: September 1989

Approximation of stochastic equations driven by predictable processes

  • Guillermo Ferreyra1 nAff2 

Probability Theory and Related Fields volume 83, pages 391–403 (1989)Cite this article

Summary

A theory of stochastic differential equations driven by predictable processes in Stratonovich sense is developed. These driving processes include a large class of discontinuous semimartingales. The theory of stochastic differential equations driven by continuous semimartingales in Stratonovich sense is extended without involving Lebesgue-Stieltjes integrals as done by Meyer. Moreover, a change of variables formula without extra terms involving the jumps of the processes holds for this theory. Results on approximation of driving processes are preserved.

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Author information

Author notes
  1. Guillermo Ferreyra

    Present address: Department of Mathematics, Luuslana State University, 70810, Baton Rouge, LA, USA

Authors and Affiliations

  1. Lefschetz Center for Dynamical Systems, Division of Applied Mathematics, Brown University, 02912, Providence, RI, USA

    Guillermo Ferreyra

Authors
  1. Guillermo Ferreyra
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Additional information

Research partially supported by the Institute for Mathematics and its Applications at the University of Minnesota, Minneapolis, USA; by the AFOSR under contract #AFOSR-85-0315, the ARO under contract #DAAG 29-84-K-0082, and #DAAL 03-86-K-0171.

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Ferreyra, G. Approximation of stochastic equations driven by predictable processes. Probab. Th. Rel. Fields 83, 391–403 (1989). https://doi.org/10.1007/BF00964371

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  • Received: 16 November 1987

  • Revised: 20 March 1989

  • Issue Date: September 1989

  • DOI: https://doi.org/10.1007/BF00964371

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Keywords

  • Differential Equation
  • Stochastic Process
  • Probability Theory
  • Large Class
  • Mathematical Biology
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