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Numerical Analysis for Stochastic Investment System with Poisson Jumps

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Advanced Intelligent Computing Theories and Applications (ICIC 2010)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 93))

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Abstract

Stochastic neutral technical progress and investment system with Poisson jumps are considered in this paper. In general most of stochastic investment system with jumps do not have explicit solutions, thus numerical approximation schemes are invaluable tools for exploring their properties. The main purpose of this paper is to develop a numerical Euler scheme and show the convergence of the numerical approximation solution to the true solution by using It\(\hat{o}\) formula and Burkholder-Davis-Gundy inequality.

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Author information

Authors and Affiliations

  1. School of Mathematics and Computer Science, Ningxia University, Yinchuan, 750021, China

    Zhanping Wang

Authors
  1. Zhanping Wang
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Editor information

Editors and Affiliations

  1. Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei, Anhui,, China

    De-Shuang Huang

  2. School of Computing and Intelligent Systems, University of Ulster at Magee Campus, BT48 7JL, Derry, Northern Ireland, UK

    Martin McGinnity

  3. Laboratoire LITIS, Université de Rouen, 76800, Saint Etienne du Rouvray, France

    Laurent Heutte

  4. Department of Electrical and Computer Engineering, Ryerson University, Toronto, Ontario, Canada

    Xiao-Ping Zhang

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Wang, Z. (2010). Numerical Analysis for Stochastic Investment System with Poisson Jumps. In: Huang, DS., McGinnity, M., Heutte, L., Zhang, XP. (eds) Advanced Intelligent Computing Theories and Applications. ICIC 2010. Communications in Computer and Information Science, vol 93. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14831-6_58

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  • DOI: https://doi.org/10.1007/978-3-642-14831-6_58

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-14830-9

  • Online ISBN: 978-3-642-14831-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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