Open AccessCryptocurrency Price Prediction with Neural Networks of LSTM and Bayesian Optimization
Author(s) -
Ehsan Sadeghi Pour,
Hossein Jafari,
Ali Lashgari,
Elaheh Rabiee,
Amin Ahmadisharaf
Publication year - 2022
Publication title -
european journal of business and management research
Language(s) - English
Resource type - Journals
ISSN - 2507-1076
DOI - 10.24018/ejbmr.2022.7.2.1307
Subject(s) - cryptocurrency , artificial neural network , computer science , bayesian probability , artificial intelligence , machine learning , bayesian optimization , predictive power , bayesian network , econometrics , economics , philosophy , computer security , epistemology
In this paper we present a price prediction for Bitcoin prices. The methodology used is a hybrid artificial neural network model of Long Short-Term Memory and Bayesian Optimization. This is a complex model with a high prediction power, which to our knowledge has not been applied to prediction of cryptocurrency prices to date. Following Charandabi and Kamyar (2021), we elaborate on previous methods used for prediction of cryptocurrency prices and build on their methodology. We conclude with detailed graphs and tables of optimization results.