Hybrid Deep Learning Model Integrating Attention Mechanism for the Accurate Prediction and Forecasting of the Cryptocurrency Market
Author
Abstract
Suggested Citation
DOI: 10.1007/s43069-024-00302-2
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- Nikolay Archak & Anindya Ghose & Panagiotis G. Ipeirotis, 2011. "Deriving the Pricing Power of Product Features by Mining Consumer Reviews," Management Science, INFORMS, vol. 57(8), pages 1485-1509, August.
- Song, Jung Yoon & Chang, Woojin & Song, Jae Wook, 2019. "Cluster analysis on the structure of the cryptocurrency market via Bitcoin–Ethereum filtering," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 527(C).
- Chuen Yik Kang & Chin Poo Lee & Kian Ming Lim, 2022. "Cryptocurrency Price Prediction with Convolutional Neural Network and Stacked Gated Recurrent Unit," Data, MDPI, vol. 7(11), pages 1-13, October.
- Borri, Nicola & Shakhnov, Kirill, 2020. "Regulation spillovers across cryptocurrency markets," Finance Research Letters, Elsevier, vol. 36(C).
- Taewook Kim & Ha Young Kim, 2019. "Forecasting stock prices with a feature fusion LSTM-CNN model using different representations of the same data," PLOS ONE, Public Library of Science, vol. 14(2), pages 1-23, February.
- Lahmiri, Salim & Bekiros, Stelios, 2019. "Cryptocurrency forecasting with deep learning chaotic neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 118(C), pages 35-40.
- Kateryna Solodan, 2019. "Legal Regulation Of Cryptocurrency Taxation in European Countries," European Journal of Law and Public Administration, Editura LUMEN, vol. 6(1), pages 64-74, September.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Kate Murray & Andrea Rossi & Diego Carraro & Andrea Visentin, 2023. "On Forecasting Cryptocurrency Prices: A Comparison of Machine Learning, Deep Learning, and Ensembles," Forecasting, MDPI, vol. 5(1), pages 1-14, January.
- Lahmiri, Salim & Bekiros, Stelios, 2020. "Intelligent forecasting with machine learning trading systems in chaotic intraday Bitcoin market," Chaos, Solitons & Fractals, Elsevier, vol. 133(C).
- Ren, Yi-Shuai & Ma, Chao-Qun & Kong, Xiao-Lin & Baltas, Konstantinos & Zureigat, Qasim, 2022. "Past, present, and future of the application of machine learning in cryptocurrency research," Research in International Business and Finance, Elsevier, vol. 63(C).
- Baxendale, Shane & Macdonald, Emma K. & Wilson, Hugh N., 2015. "The Impact of Different Touchpoints on Brand Consideration," Journal of Retailing, Elsevier, vol. 91(2), pages 235-253.
- Wu, Xingli & Liao, Huchang, 2021. "Modeling personalized cognition of customers in online shopping," Omega, Elsevier, vol. 104(C).
- Méndez-Gordillo, Alma Rosa & Cadenas, Erasmo, 2021. "Wind speed forecasting by the extraction of the multifractal patterns of time series through the multiplicative cascade technique," Chaos, Solitons & Fractals, Elsevier, vol. 143(C).
- Chowdhury, Reaz & Rahman, M. Arifur & Rahman, M. Sohel & Mahdy, M.R.C., 2020. "An approach to predict and forecast the price of constituents and index of cryptocurrency using machine learning," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 551(C).
- Jiyeon Hong & Paul R. Hoban, 2022. "Writing More Compelling Creative Appeals: A Deep Learning-Based Approach," Marketing Science, INFORMS, vol. 41(5), pages 941-965, September.
- Gökçe Esenduran & James A. Hill & In Joon Noh, 2020. "Understanding the Choice of Online Resale Channel for Used Electronics," Production and Operations Management, Production and Operations Management Society, vol. 29(5), pages 1188-1211, May.
- Schneider, Matthew J. & Gupta, Sachin, 2016. "Forecasting sales of new and existing products using consumer reviews: A random projections approach," International Journal of Forecasting, Elsevier, vol. 32(2), pages 243-256.
- Parisa Foroutan & Salim Lahmiri, 2024. "Connectedness of cryptocurrency markets to crude oil and gold: an analysis of the effect of COVID-19 pandemic," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-23, December.
- Yufei Zhang & Clay M. Voorhees & G. Tomas M. Hult, 2024. "Dynamic interplays between online reviews and marketing promotions," Journal of the Academy of Marketing Science, Springer, vol. 52(6), pages 1820-1841, November.
- Paul Handro & Bogdan Dima, 2024. "Analyzing Financial Markets Efficiency: Insights from a Bibliometric and Content Review," Journal of Financial Studies, Institute of Financial Studies, vol. 16(9), pages 119-175, May.
- Borchert, Philipp & Coussement, Kristof & De Weerdt, Jochen & De Caigny, Arno, 2024. "Industry-sensitive language modeling for business," European Journal of Operational Research, Elsevier, vol. 315(2), pages 691-702.
- Cao, Guangxi & Xie, Wenhao, 2022. "Asymmetric dynamic spillover effect between cryptocurrency and China's financial market: Evidence from TVP-VAR based connectedness approach," Finance Research Letters, Elsevier, vol. 49(C).
- Flori, Andrea, 2019. "News and subjective beliefs: A Bayesian approach to Bitcoin investments," Research in International Business and Finance, Elsevier, vol. 50(C), pages 336-356.
- Tashreef Muhammad & Tahsin Aziz & Mohammad Shafiul Alam, 2023. "Utilizing Technical Data to Discover Similar Companies in Dhaka Stock Exchange," Papers 2301.04455, arXiv.org.
- Younghoon Lee, 2022. "Identifying Competitive Attributes Based on an Ensemble of Explainable Artificial Intelligence," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 64(4), pages 407-419, August.
- Jun Hwan Kim & Hyun Cheol Lee, 2019. "Understanding the Repurchase Intention of Premium Economy Passengers Using an Extended Theory of Planned Behavior," Sustainability, MDPI, vol. 11(11), pages 1-19, June.
- Copestake, Alexander & Furceri, Davide & Gonzalez-Dominguez, Pablo, 2023. "Crypto market responses to digital asset policies," Economics Letters, Elsevier, vol. 222(C).
More about this item
Keywords
Attention Mechanism; BTC-USD; CNN; ETH-USD; LSTM;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:snopef:v:5:y:2024:i:1:d:10.1007_s43069-024-00302-2. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.