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Heterogeneous Agents Past and Forward Time Horizons in Setting Up a Computational Model

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  • Serge Hayward

Abstract

Price forecasting and trading strategies modelling are examined with major international stock indexes under different time horizons. Results demonstrate that an accurate prediction is equally important as a stable saving rate for long-term survivability. The best economic performances are achieved for a one-year investment horizon with longer training not necessarily leading to improved accuracy. Thin markets" dominance by a particular traders" type (e.g. short memory agents) results in a higher likelihood to learn with computational intelligence tools profitable strategies, used by dominant traders. An improvement in profitability is achieved for models optimized with genetic algorithm and fine-tuning of training/validation/testing distribution

Suggested Citation

  • Serge Hayward, 2004. "Heterogeneous Agents Past and Forward Time Horizons in Setting Up a Computational Model," Computing in Economics and Finance 2004 241, Society for Computational Economics.
  • Handle: RePEc:sce:scecf4:241
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    File URL: http://repec.org/sce2004/up.5449.1077915422.pdf
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    References listed on IDEAS

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    1. Sweeney, Richard J., 1988. "Some New Filter Rule Tests: Methods and Results," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 23(03), pages 285-300, September.
    2. Blume, Lawrence & Easley, David, 1992. "Evolution and market behavior," Journal of Economic Theory, Elsevier, vol. 58(1), pages 9-40, October.
    3. Ya-Chi Huang & Shu-Heng Chen, 2003. "Simulating the Evolution of Portfolio Behavior in a Multiple-Asset Agent-Based Artificial Stock Market," Computing in Economics and Finance 2003 62, Society for Computational Economics.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Artificial Neural Network; Genetic Algorithm; Heterogeneous Agents; Time Horizons; Memory Length; Economic Profitability; Statistical Accuracy; Financial Markets; Stock Trading Strategies;

    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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