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Continuous Extension of Euler-Maruyama Method for Stochastic Differential Equations

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Computational Science and Its Applications – ICCSA 2021 (ICCSA 2021)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12949))

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Abstract

In this work we focus on the development of continuous extension of Euler-Maruyama method, which is used to numerically approximate the solution of Stochastic Differential Equations (SDEs). We aim to provide an approximation of a given SDE in terms of a piecewise polynomial, because, as it is known in the deterministic case, a dense output allows to provide a more efficient error estimate and it is very effective for a variable step-size implementation. Hence, this contribution aims to provide a first building block in such directions, consisting in the development of the scheme.

The authors are members of the GNCS group. This work is supported by GNCS-INDAM project and by PRIN2017-MIUR project.

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Author information

Authors and Affiliations

  1. Department of Mathematics, University of Salerno, Fisciano, Italy

    Dajana Conte, Giuseppe Giordano & Beatrice Paternoster

  2. DISIM, University of L’Aquila, L’Aquila, Italy

    Raffaele D’Ambrosio

Authors
  1. Dajana Conte
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  2. Raffaele D’Ambrosio
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  3. Giuseppe Giordano
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  4. Beatrice Paternoster
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Corresponding author

Correspondence to Giuseppe Giordano .

Editor information

Editors and Affiliations

  1. University of Perugia, Perugia, Italy

    Osvaldo Gervasi

  2. University of Basilicata, Potenza, Potenza, Italy

    Beniamino Murgante

  3. Covenant University, Ota, Nigeria

    Sanjay Misra

  4. University of Cagliari, Cagliari, Italy

    Chiara Garau

  5. University of Cagliari, Cagliari, Italy

    Ivan Blečić

  6. Monash University, Clayton, VIC, Australia

    David Taniar

  7. Kyushu Sangyo University, Fukuoka, Japan

    Bernady O. Apduhan

  8. University of Minho, Braga, Portugal

    Ana Maria A. C. Rocha

  9. Polytechnic University of Bari, Bari, Italy

    Eufemia Tarantino

  10. Polytechnic University of Bari, Bari, Italy

    Carmelo Maria Torre

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Conte, D., D’Ambrosio, R., Giordano, G., Paternoster, B. (2021). Continuous Extension of Euler-Maruyama Method for Stochastic Differential Equations. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2021. ICCSA 2021. Lecture Notes in Computer Science(), vol 12949. Springer, Cham. https://doi.org/10.1007/978-3-030-86653-2_10

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  • DOI: https://doi.org/10.1007/978-3-030-86653-2_10

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