Intelligent method to cryptocurrency price variation forecasting

  • Farsangi M
  • Keynia F
  • Farsangi E
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Abstract

Nowadays, accurate prediction of cryptocurrency price variation based on their important role in the world economy is an important and challenging issue. In this study, various parameters that affect the cryptocurrency value have been considered. For the first phase, four major price features of digital currencies have been analysed to determine the effect of each feature on the volatility prediction of future days. This study aims to understand and identify daily trends in the cryptocurrency market while gaining insight into optimal features surrounding their price. For the second phase, the price variation has been predicted with the highest possible accuracy with a new intelligent method. The proposed method consists of a neural network-based prediction algorithm and particle swarm optimisation. The obtained results show the capbility of the proposed method. © This is an open access article published by the IET under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/)

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Farsangi, M. N., Keynia, F., & Farsangi, E. N. (2020). Intelligent method to cryptocurrency price variation forecasting. The Journal of Engineering, 2020(9), 745–750. https://doi.org/10.1049/joe.2019.1236

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