Manuscript Number : IJSRST52310588

Cryptocurrency Price Prediction Deep Learning

Authors(6) :-Aditya Dahatonde, Lajwanti Kute, Yash Shinde, Chetan Chavan, Dheeraj Patil, Chandrakant Kokane

Cryptocurrencies are changing how we view and interact with traditional currencies, and they have become a disruptive force in the financial industry. Accurate price prediction is becoming more and more important as the bitcoin industry grows in size and complexity. This paper provides a thorough examination of deep learning models used in bitcoin price prediction. We explore the dynamic and unpredictable character of the cryptocurrency market, where price swings can happen quickly and without warning. To comprehend the present state of the art in this domain and pinpoint the shortcomings of the deep learning models in use today, we examine the body of existing literature. The data collecting and preprocessing methods used to get the bitcoin market data ready for modeling are described in the methodology section. Numerous deep learning models—Recurrent Neural Networks among them, Convolutional neural networks (CNNs) and Long Short-Term Memory (LSTM) networks are investigated. We go over hyperparameter tweaking, model training, and the assessment metrics that are used to gauge the performance of the model. We offer a thorough case study that focuses on forecasting the price of a particular cryptocurrency, like Bitcoin, in order to offer empirical insights. Our results provide light on the difficulties and possibilities involved in this project, emphasizing the need for creative solutions to address the market's uncertainties. We highlight the limitations and the necessity for additional research and innovation in the field of bitcoin price prediction as we outline the main lessons learned in the conclusion. We also discuss the consequences of using deep learning models to risk management in bitcoin investment and trading.

Authors and Affiliations

Aditya Dahatonde
Nutan Maharashtra Institute of Engineering and Technology, Talegaon(D), Pune, Maharashtra, India
Lajwanti Kute
Nutan Maharashtra Institute of Engineering and Technology, Talegaon(D), Pune, Maharashtra, India
Yash Shinde
Nutan Maharashtra Institute of Engineering and Technology, Talegaon(D), Pune, Maharashtra, India
Chetan Chavan
Nutan Maharashtra Institute of Engineering and Technology, Talegaon(D), Pune, Maharashtra, India
Dheeraj Patil
Nutan Maharashtra Institute of Engineering and Technology, Talegaon(D), Pune, Maharashtra, India
Chandrakant Kokane
Nutan Maharashtra Institute of Engineering and Technology, Talegaon(D), Pune, Maharashtra, India

Natural Language Processing, Deep Learning

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  2. U. Suliman, T. L. van Zyl, and A. Paskaramoorthy, "Cryptocurrency Trading Agent Using Deep Reinforcement Learning," 2022 9th International Conference on Soft Computing & Machine Intelligence (ISCMI), Toronto, ON, Canada, 2022, pp. 1-5, doi: 10.1109/ISCMI56532.2022.10068485.
  3. A. Armin, A. Shiri, and B. Bahrak, "Comparison of Machine Learning Methods for Cryptocurrency Price Prediction," 2022 8th Iranian Conference on Signal Processing and Intelligent Systems (ICSPIS), Behshahr, Iran, Islamic Republic of, 2022, pp. 1-6, doi: 10.1109/ICSPIS56952.2022.10043898.
  4. D. K. Tejaswi and H. Chauhan, "Investigation of Ethereum Price Trends using Machine learning and Deep Learning Algorithms," 2022 2nd International Conference on Intelligent Technologies (CONIT), Hubli, India, 2022, pp. 1-6, doi: 10.1109/CONIT55038.2022.9848000.
  5. S. Biswas, M. Pawar, and S. Badole, "Cryptocurrency Price Prediction Using Neural Networks and Deep Learning," 2021 7th International Conference on Advanced Computing and Communication Systems (ICACCS), Coimbatore, India, 2021, pp. 1-6, doi: 10.1109/ICACCS51430.2021.9441872.
  6. V. K. T, S. Santhi, K. G. Shanthi, and G. M, "Cryptocurrency Price Prediction using LSTM and Recurrent Neural Networks," 2023 2nd International Conference on Applied Artificial Intelligence and Computing (ICAAIC), Salem, India, 2023, pp. 1-5, doi: 10.1109/ICAAIC56838.2023.10141048.
  7. N. T. Cao, D. Q. Nguyen, and A. H. Ton-That, "A Combination of Technical Indicators and Deep Learning to Predict Price Trends for Short-Term Cryptocurrency Investment," 2022 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE), Gold Coast, Australia, 2022, pp. 1-6, doi: 10.1109/CSDE56538.2022.10089300.
  8. T. Zuvela, S. Lazarevic, and S. Djordjevic, "Cryptocurrency Price Prediction Using Deep Learning," 2022 IEEE 16th International Symposium on Applied Computational Intelligence and Informatics (SACI), Timisoara, Romania, 2022, pp. 1-6, doi: 10.1109/SACI55618.2022.9919554.
  9. Kokane, Chandrakant D., and Sachin D. Babar. "Supervised word sense disambiguation with recurrent neural network model." Int. J. Eng. Adv. Technol.(IJEAT) 9.2 (2019).
  10. Kokane, Chandrakant D., Sachin D. Babar, and Parikshit N. Mahalle. "Word Sense Disambiguation for Large Documents Using Neural Network Model." 2021 12th International Conference on Computing Communication and Networking Technologies (ICCCNT). IEEE, 2021.
  11. Kokane, Chandrakant, et al. "Word Sense Disambiguation: A Supervised Semantic Similarity based Complex Network Approach." International Journal of Intelligent Systems and Applications in Engineering 10.1s (2022): 90-94.
  12. Kokane, Chandrakant D., et al. "Machine Learning Approach for Intelligent Transport System in IOV-Based Vehicular Network Traffic for Smart Cities." International Journal of Intelligent Systems and Applications in Engineering 11.11s (2023): 06-16.
  13. Kokane, Chandrakant D., et al. "Word Sense Disambiguation: Adaptive Word Embedding with Adaptive-Lexical Resource." International Conference on Data Analytics and Insights. Singapore: Springer Nature Singapore, 2023.

Publication Details

Published in : Volume 10 | Issue 6 | November-December 2023
Date of Publication : 2023-12-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 263-267
Manuscript Number : IJSRST52310588
Publisher : Technoscience Academy

Print ISSN : 2395-6011, Online ISSN : 2395-602X

Cite This Article :

Aditya Dahatonde, Lajwanti Kute, Yash Shinde, Chetan Chavan, Dheeraj Patil, Chandrakant Kokane, " Cryptocurrency Price Prediction Deep Learning", International Journal of Scientific Research in Science and Technology(IJSRST), Print ISSN : 2395-6011, Online ISSN : 2395-602X, Volume 10, Issue 6, pp.263-267, November-December-2023.
Journal URL : https://ijsrst.com/IJSRST52310588
Citation Detection and Elimination     |      | |
  • U. Suliman, T. L. van Zyl, and A. Paskaramoorthy, "Cryptocurrency Trading Agent Using Deep Reinforcement Learning," 2022 9th International Conference on Soft Computing & Machine Intelligence (ISCMI), Toronto, ON, Canada, 2022, pp. 1-5, doi: 10.1109/ISCMI56532.2022.10068485.
  • A. Armin, A. Shiri, and B. Bahrak, "Comparison of Machine Learning Methods for Cryptocurrency Price Prediction," 2022 8th Iranian Conference on Signal Processing and Intelligent Systems (ICSPIS), Behshahr, Iran, Islamic Republic of, 2022, pp. 1-6, doi: 10.1109/ICSPIS56952.2022.10043898.
  • D. K. Tejaswi and H. Chauhan, "Investigation of Ethereum Price Trends using Machine learning and Deep Learning Algorithms," 2022 2nd International Conference on Intelligent Technologies (CONIT), Hubli, India, 2022, pp. 1-6, doi: 10.1109/CONIT55038.2022.9848000.
  • S. Biswas, M. Pawar, and S. Badole, "Cryptocurrency Price Prediction Using Neural Networks and Deep Learning," 2021 7th International Conference on Advanced Computing and Communication Systems (ICACCS), Coimbatore, India, 2021, pp. 1-6, doi: 10.1109/ICACCS51430.2021.9441872.
  • V. K. T, S. Santhi, K. G. Shanthi, and G. M, "Cryptocurrency Price Prediction using LSTM and Recurrent Neural Networks," 2023 2nd International Conference on Applied Artificial Intelligence and Computing (ICAAIC), Salem, India, 2023, pp. 1-5, doi: 10.1109/ICAAIC56838.2023.10141048.
  • N. T. Cao, D. Q. Nguyen, and A. H. Ton-That, "A Combination of Technical Indicators and Deep Learning to Predict Price Trends for Short-Term Cryptocurrency Investment," 2022 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE), Gold Coast, Australia, 2022, pp. 1-6, doi: 10.1109/CSDE56538.2022.10089300.
  • T. Zuvela, S. Lazarevic, and S. Djordjevic, "Cryptocurrency Price Prediction Using Deep Learning," 2022 IEEE 16th International Symposium on Applied Computational Intelligence and Informatics (SACI), Timisoara, Romania, 2022, pp. 1-6, doi: 10.1109/SACI55618.2022.9919554.
  • Kokane, Chandrakant D., and Sachin D. Babar. "Supervised word sense disambiguation with recurrent neural network model." Int. J. Eng. Adv. Technol.(IJEAT) 9.2 (2019).
  • Kokane, Chandrakant D., Sachin D. Babar, and Parikshit N. Mahalle. "Word Sense Disambiguation for Large Documents Using Neural Network Model." 2021 12th International Conference on Computing Communication and Networking Technologies (ICCCNT). IEEE, 2021.
  • Kokane, Chandrakant, et al. "Word Sense Disambiguation: A Supervised Semantic Similarity based Complex Network Approach." International Journal of Intelligent Systems and Applications in Engineering 10.1s (2022): 90-94.
  • Kokane, Chandrakant D., et al. "Machine Learning Approach for Intelligent Transport System in IOV-Based Vehicular Network Traffic for Smart Cities." International Journal of Intelligent Systems and Applications in Engineering 11.11s (2023): 06-16.
  • Kokane, Chandrakant D., et al. "Word Sense Disambiguation: Adaptive Word Embedding with Adaptive-Lexical Resource." International Conference on Data Analytics and Insights. Singapore: Springer Nature Singapore, 2023.
    • " target="_blank"> BibTeX     |
  • U. Suliman, T. L. van Zyl, and A. Paskaramoorthy, "Cryptocurrency Trading Agent Using Deep Reinforcement Learning," 2022 9th International Conference on Soft Computing & Machine Intelligence (ISCMI), Toronto, ON, Canada, 2022, pp. 1-5, doi: 10.1109/ISCMI56532.2022.10068485.
  • A. Armin, A. Shiri, and B. Bahrak, "Comparison of Machine Learning Methods for Cryptocurrency Price Prediction," 2022 8th Iranian Conference on Signal Processing and Intelligent Systems (ICSPIS), Behshahr, Iran, Islamic Republic of, 2022, pp. 1-6, doi: 10.1109/ICSPIS56952.2022.10043898.
  • D. K. Tejaswi and H. Chauhan, "Investigation of Ethereum Price Trends using Machine learning and Deep Learning Algorithms," 2022 2nd International Conference on Intelligent Technologies (CONIT), Hubli, India, 2022, pp. 1-6, doi: 10.1109/CONIT55038.2022.9848000.
  • S. Biswas, M. Pawar, and S. Badole, "Cryptocurrency Price Prediction Using Neural Networks and Deep Learning," 2021 7th International Conference on Advanced Computing and Communication Systems (ICACCS), Coimbatore, India, 2021, pp. 1-6, doi: 10.1109/ICACCS51430.2021.9441872.
  • V. K. T, S. Santhi, K. G. Shanthi, and G. M, "Cryptocurrency Price Prediction using LSTM and Recurrent Neural Networks," 2023 2nd International Conference on Applied Artificial Intelligence and Computing (ICAAIC), Salem, India, 2023, pp. 1-5, doi: 10.1109/ICAAIC56838.2023.10141048.
  • N. T. Cao, D. Q. Nguyen, and A. H. Ton-That, "A Combination of Technical Indicators and Deep Learning to Predict Price Trends for Short-Term Cryptocurrency Investment," 2022 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE), Gold Coast, Australia, 2022, pp. 1-6, doi: 10.1109/CSDE56538.2022.10089300.
  • T. Zuvela, S. Lazarevic, and S. Djordjevic, "Cryptocurrency Price Prediction Using Deep Learning," 2022 IEEE 16th International Symposium on Applied Computational Intelligence and Informatics (SACI), Timisoara, Romania, 2022, pp. 1-6, doi: 10.1109/SACI55618.2022.9919554.
  • Kokane, Chandrakant D., and Sachin D. Babar. "Supervised word sense disambiguation with recurrent neural network model." Int. J. Eng. Adv. Technol.(IJEAT) 9.2 (2019).
  • Kokane, Chandrakant D., Sachin D. Babar, and Parikshit N. Mahalle. "Word Sense Disambiguation for Large Documents Using Neural Network Model." 2021 12th International Conference on Computing Communication and Networking Technologies (ICCCNT). IEEE, 2021.
  • Kokane, Chandrakant, et al. "Word Sense Disambiguation: A Supervised Semantic Similarity based Complex Network Approach." International Journal of Intelligent Systems and Applications in Engineering 10.1s (2022): 90-94.
  • Kokane, Chandrakant D., et al. "Machine Learning Approach for Intelligent Transport System in IOV-Based Vehicular Network Traffic for Smart Cities." International Journal of Intelligent Systems and Applications in Engineering 11.11s (2023): 06-16.
  • Kokane, Chandrakant D., et al. "Word Sense Disambiguation: Adaptive Word Embedding with Adaptive-Lexical Resource." International Conference on Data Analytics and Insights. Singapore: Springer Nature Singapore, 2023.
    • " target="_blank">RIS     |
  • U. Suliman, T. L. van Zyl, and A. Paskaramoorthy, "Cryptocurrency Trading Agent Using Deep Reinforcement Learning," 2022 9th International Conference on Soft Computing & Machine Intelligence (ISCMI), Toronto, ON, Canada, 2022, pp. 1-5, doi: 10.1109/ISCMI56532.2022.10068485.
  • A. Armin, A. Shiri, and B. Bahrak, "Comparison of Machine Learning Methods for Cryptocurrency Price Prediction," 2022 8th Iranian Conference on Signal Processing and Intelligent Systems (ICSPIS), Behshahr, Iran, Islamic Republic of, 2022, pp. 1-6, doi: 10.1109/ICSPIS56952.2022.10043898.
  • D. K. Tejaswi and H. Chauhan, "Investigation of Ethereum Price Trends using Machine learning and Deep Learning Algorithms," 2022 2nd International Conference on Intelligent Technologies (CONIT), Hubli, India, 2022, pp. 1-6, doi: 10.1109/CONIT55038.2022.9848000.
  • S. Biswas, M. Pawar, and S. Badole, "Cryptocurrency Price Prediction Using Neural Networks and Deep Learning," 2021 7th International Conference on Advanced Computing and Communication Systems (ICACCS), Coimbatore, India, 2021, pp. 1-6, doi: 10.1109/ICACCS51430.2021.9441872.
  • V. K. T, S. Santhi, K. G. Shanthi, and G. M, "Cryptocurrency Price Prediction using LSTM and Recurrent Neural Networks," 2023 2nd International Conference on Applied Artificial Intelligence and Computing (ICAAIC), Salem, India, 2023, pp. 1-5, doi: 10.1109/ICAAIC56838.2023.10141048.
  • N. T. Cao, D. Q. Nguyen, and A. H. Ton-That, "A Combination of Technical Indicators and Deep Learning to Predict Price Trends for Short-Term Cryptocurrency Investment," 2022 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE), Gold Coast, Australia, 2022, pp. 1-6, doi: 10.1109/CSDE56538.2022.10089300.
  • T. Zuvela, S. Lazarevic, and S. Djordjevic, "Cryptocurrency Price Prediction Using Deep Learning," 2022 IEEE 16th International Symposium on Applied Computational Intelligence and Informatics (SACI), Timisoara, Romania, 2022, pp. 1-6, doi: 10.1109/SACI55618.2022.9919554.
  • Kokane, Chandrakant D., and Sachin D. Babar. "Supervised word sense disambiguation with recurrent neural network model." Int. J. Eng. Adv. Technol.(IJEAT) 9.2 (2019).
  • Kokane, Chandrakant D., Sachin D. Babar, and Parikshit N. Mahalle. "Word Sense Disambiguation for Large Documents Using Neural Network Model." 2021 12th International Conference on Computing Communication and Networking Technologies (ICCCNT). IEEE, 2021.
  • Kokane, Chandrakant, et al. "Word Sense Disambiguation: A Supervised Semantic Similarity based Complex Network Approach." International Journal of Intelligent Systems and Applications in Engineering 10.1s (2022): 90-94.
  • Kokane, Chandrakant D., et al. "Machine Learning Approach for Intelligent Transport System in IOV-Based Vehicular Network Traffic for Smart Cities." International Journal of Intelligent Systems and Applications in Engineering 11.11s (2023): 06-16.
  • Kokane, Chandrakant D., et al. "Word Sense Disambiguation: Adaptive Word Embedding with Adaptive-Lexical Resource." International Conference on Data Analytics and Insights. Singapore: Springer Nature Singapore, 2023.
    • " target="_blank">CSV

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