Open AccessIntelligent method to cryptocurrency price variation forecasting
Author(s) -
Farsangi Mohsen Noroozinejad,
Keynia Farshid,
Farsangi Ehsan Noroozinejad
Publication year - 2020
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2019.1236
Subject(s) - cryptocurrency , volatility (finance) , computer science , variation (astronomy) , artificial neural network , econometrics , particle swarm optimization , feature (linguistics) , artificial intelligence , machine learning , economics , computer security , physics , astrophysics , linguistics , philosophy
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.