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Weak Discrete Time Approximation of Stochastic Differential Equations with Time Delay

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Abstract

The paper considers the derivation of weak discrete time approximations for solutions of stochastic differential equations with time delay. These are suitable for Monte Carlo simulation and allow the computation of expectations for functionals of stochastic delay equations. The suggested approximations converge in a weak sense.

Suggested Citation

  • Uwe Kuchler & Eckhard Platen, 2001. "Weak Discrete Time Approximation of Stochastic Differential Equations with Time Delay," Research Paper Series 50, Quantitative Finance Research Centre, University of Technology, Sydney.
  • Handle: RePEc:uts:rpaper:50
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    File URL: http://www.qfrc.uts.edu.au/research/research_papers/rp50.pdf
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    References listed on IDEAS

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    1. Küchler, Uwe & Platen, Eckhard, 2000. "Strong discrete time approximation of stochastic differential equations with time delay," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 54(1), pages 189-205.
    2. Eckhard Platen, 1999. "An Introduction to Numerical Methods for Stochastic Differential Equations," Research Paper Series 6, Quantitative Finance Research Centre, University of Technology, Sydney.
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    Cited by:

    1. Ghassan Dibeh & Haidar Harmanani, 2012. "A Stochastic Chartist–Fundamentalist Model with Time Delays," Computational Economics, Springer;Society for Computational Economics, vol. 40(2), pages 105-113, August.
    2. Yu, Wenwu & Cao, Jinde, 2007. "Synchronization control of stochastic delayed neural networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 373(C), pages 252-260.
    3. Uwe Küchler & Eckhard Platen, 2007. "Time Delay and Noise Explaining Cyclical Fluctuations in Prices of Commodities," Research Paper Series 195, Quantitative Finance Research Centre, University of Technology, Sydney.

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