Prediction of cryptocurrency prices by deep learning models: A case study for Bitcoin and Ethereum

被引:0
|
作者
Mehrdoust, Farshid [1 ]
Noorani, Maryam [1 ]
机构
[1] Univ Guilan, Fac Math Sci, Dept Appl Math, Rasht 419381914, Iran
关键词
Cryptocurrency prices; deep learning; machine learning; prediction models; PERFORMANCE;
D O I
10.1142/S2424786323500329
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
Cryptocurrency prediction is important for a variety of stakeholders, from investors to businesses, as it enables them to make more informed decisions about the future of the digital asset market. This paper delves into the application of deep learning models for two of the most popular cryptocurrencies, Bitcoin and Ethereum, outlining how to effectively implement these methods. Our goal is to perform efficient deep learning structure based on the forecasting models specifically recurrent neural networks, convolutional neural network and long short-term memory to predict the Bitcoin and Ethereum prices. Our results include a comparison of these two cryptocurrencies according to the deep learning methods and their effectiveness in predicting the Bitcoin and Ethereum prices.
引用
收藏
页数:18
相关论文
共 50 条
  • [1] Modelling the dynamics of cryptocurrency prices for risk hedging: The case of Bitcoin, Ethereum, and Litecoin
    Madichie, Chekwube V.
    Ngwu, Franklin N.
    Eze, Eze A.
    Maduka, Olisaemeka D.
    [J]. COGENT ECONOMICS & FINANCE, 2023, 11 (01):
  • [2] On the efficiency and its drivers in the cryptocurrency market: the case of Bitcoin and Ethereum
    Mokni, Khaled
    El Montasser, Ghassen
    Ajmi, Ahdi Noomen
    Bouri, Elie
    [J]. FINANCIAL INNOVATION, 2024, 10 (01)
  • [3] On the efficiency and its drivers in the cryptocurrency market: the case of Bitcoin and Ethereum
    Khaled Mokni
    Ghassen El Montasser
    Ahdi Noomen Ajmi
    Elie Bouri
    [J]. Financial Innovation, 10
  • [4] Structural breaks and double long memory of cryptocurrency prices: A comparative analysis from Bitcoin and Ethereum
    Mensi, Walid
    Al-Yahyaee, Khamis Hamed
    Kang, Sang Hoon
    [J]. FINANCE RESEARCH LETTERS, 2019, 29 : 222 - 230
  • [5] Cryptocurrency liquidity during the Russia-Ukraine war: the case of Bitcoin and Ethereum
    Theiri, Saliha
    Nekhili, Ramzi
    Sultan, Jahangir
    [J]. JOURNAL OF RISK FINANCE, 2023, 24 (01) : 59 - 71
  • [6] Ethereum Cryptocurrency Entry Point and Trend Prediction using Bitcoin Correlation and Multiple Data Combination
    EL Zaar, Abdellah
    Benaya, Nabil
    EL Moubtahij, Hicham
    Bakir, Toufik
    Mansouri, Amine
    EL Allati, Abderrahim
    [J]. INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2023, 14 (05) : 54 - 64
  • [7] PREDICTION OF CRYPTOCURRENCY PRICES WITH LSTM AND GRU MODELS
    Demirci, Esranur
    Karaatli, Meltem
    [J]. JOURNAL OF MEHMET AKIF ERSOY UNIVERSITY ECONOMICS AND ADMINISTRATIVE SCIENCES FACULTY, 2023, 10 (01): : 134 - 157
  • [8] Prediction of Bitcoin Prices Based on Blockchain Information: A Deep Reinforcement Learning Approach
    Khadija, Mnasri
    Fahmi, Ben Rejab
    Syrine, Ben Romdhane
    [J]. ADVANCES IN ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING, 2024, 4 (03): : 2416 - 2433
  • [9] Empirical Forecasting Analysis of Bitcoin Prices: A Comparison of Machine Learning, Deep Learning, and Ensemble Learning Models
    Tripathy, Nrusingha
    Hota, Sarbeswara
    Mishra, Debahuti
    Satapathy, Pranati
    Nayak, Subrat Kumar
    [J]. INTERNATIONAL JOURNAL OF ELECTRICAL AND COMPUTER ENGINEERING SYSTEMS, 2024, 15 (01) : 21 - 29
  • [10] Machine learning Ethereum cryptocurrency prediction and knowledge-based investment strategies
    Vieitez, Adrian
    Santos, Matilde
    Naranjo, Rodrigo
    [J]. KNOWLEDGE-BASED SYSTEMS, 2024, 299