Syrine Ben Romdhane and Mnasri Khadija
Adv. Artif. Intell. Mach. Learn., 4 (3):2416-2433
Syrine Ben Romdhane : University of Tunis, Higher Institute of Management of Tunis, BESTMOD Lab, Tunis, Tunisia
Mnasri Khadija : University of Lorraine, CEREFIGE-Lab, France
Article History: Received on: 06-May-24, Accepted on: 15-Jul-24, Published on: 22-Jul-24
Corresponding Author: Syrine Ben Romdhane
Email: syrine_br@yahoo.fr
Citation: Mnasri Khadija, et al. Prediction of Bitcoin Prices Based on Blockchain Information: A Deep Reinforcement Learning Approach. Advances in Artificial Intelligence and Machine Learning; Research 2024;4(3):141.
Bitcoin, the first
decentralized cryptocurrency, has attracted significant attention from
investors and researchers alike due to its volatile and unpredictable price
movements. However, predicting the price of Bitcoin remains a challenging task.
This paper presents a detailed literature review on previous studies that have
attempted to predict the price of Bitcoin. It discusses the main drivers of
Bitcoin prices, including its attractiveness, macroeconomic and financial
factors with a particular focus on the use of Blockchain information. We apply
time series to daily data for the period from 28/04/2013 to 28/01/2023. We used
Python and TensorFlow library version 2.11.0 and propose a deep multimodal
reinforcement learning policy combining convolutional neural network (CNN) and
long short-term memory (LSTM) neural network for cryptocurrencies’ prices
prediction. Also, this study attempts to predict the price of Bitcoin using a
special type of deep neural networks, a Deep Autoencoders. Two results are
worth noting: Autoencoders turns out to be the best method of predicting
Bitcoin prices, and Bitcoin-specific Blockchain information is the most
important variable in predicting Bitcoin prices. This study highlights the
potential utility of incorporating Blockchain factors in price prediction
models. Also, our findings show that sentiment
indicator, Ethereum, XRP and Doge Coin prices, global currency ratio,
macro-economic factors, and Blockchain information of Ethereum did not
contribute significantly toward predicting Bitcoin prices. These conclusions
provide decision support for investors and a reference for the governments to
design better regulatory policies.