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Using Genetic Algorithm and NARX Neural Network to Forecast Daily Bitcoin Price

Author

Listed:
  • Jin-Bom Han

    () (Kim Il Sung University)

  • Sun-Hak Kim

    (Kim Il Sung University)

  • Myong-Hun Jang

    (Kim Il Sung University)

  • Kum-Sun Ri

    (Kim Il Sung University)

Abstract

The main purpose of this paper is to suggest daily bitcoin return model using a genetic algorithm and NARX neural network. We found that the genetic algorithm is effective to decide the architecture of the NARX neural network than information criteria-Akaike information criterion and the Schwarz information criterion using a Monte Carlo simulation and a hypothesis test. Finally, we forecasted daily bitcoin geometric return using this hybrid model of the genetic algorithm and NARX neural network and compare it with a feed-forward neural network forecasting model through a hypothesis test.

Suggested Citation

  • Jin-Bom Han & Sun-Hak Kim & Myong-Hun Jang & Kum-Sun Ri, 2020. "Using Genetic Algorithm and NARX Neural Network to Forecast Daily Bitcoin Price," Computational Economics, Springer;Society for Computational Economics, vol. 56(2), pages 337-353, August.
    • Handle: RePEc:kap:compec:v:56:y:2020:i:2:d:10.1007_s10614-019-09928-5
    DOI: 10.1007/s10614-019-09928-5
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    References listed on IDEAS

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    Cited by:

    1. Yang, Boyu & Sun, Yuying & Wang, Shouyang, 2020. "A novel two-stage approach for cryptocurrency analysis," International Review of Financial Analysis, Elsevier, vol. 72(C).

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