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Futures Trend Strategy Model Based on Recurrent Neural Network

Author

Listed:
  • Ru Zhang
  • Chenyu Huang
  • Shaozhen Chen

Abstract

In recent years, quantitative investment has been widely used in the global futures market, and its steady investment performance has also been recognized by domestic futures investors. This paper takes the CSI-300 stock index futures as the research object and constructs a futures trend strategy model based on recurrent neural network. Furthermore, this paper back tests the strategy at different periods, different transaction costs and different parameters. The results show that the strategy model has strong profitability and robustness.

Suggested Citation

  • Ru Zhang & Chenyu Huang & Shaozhen Chen, 2018. "Futures Trend Strategy Model Based on Recurrent Neural Network," Applied Economics and Finance, Redfame publishing, vol. 5(4), pages 95-101, July.
    • Handle: RePEc:rfa:aefjnl:v:5:y:2018:i:4:p:95-101
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    Cited by:

    1. Farnaz Ghashami & Kamyar Kamyar & S. Ali Riazi, 2021. "Prediction of Stock Market Index Using a Hybrid Technique of Artificial Neural Networks and Particle Swarm Optimization," Applied Economics and Finance, Redfame publishing, vol. 8(3), pages 1-8, December.

    More about this item

    Keywords

    futures trend strategy; recurrent neural network; quantitative trading;
    All these keywords.

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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