BITCOIN PRICE PREDICTION WITH COVID-19 SENTIMENT USING LSTM NEURAL NETWORK
Keywords:Supervised learning, Neural Networks, Back Propagation, Long Short term Memory, Gated Recurrent Unit
Cryptocurrencies are nowadays getting popular for investment due to its various benefits such as low transaction cost, blockchain secured platform, profit, etc. Bitcoin being top of the market capitalization currency, gained more popularity during covid-19 pandemic. This study focuses on bitcoin price prediction with covid-19 sentiment. Here Long Short Term Memory Deep learning model based on machine learning is used for price prediction. At the end both results i.e., with covid-19 sentiment and without it are compared which shows model performs better by adding sentiments.
Achyut, G. Soumik, B. Giridhar, M. Narayan, C. & Somya, S. (2019). Stock Price Prediction Using LSTM on Indian Share Market. 32nd International Conference on Computer Applications in Industry and Engineering, 63, 101-110. https://easychair.org/publications/open/LKgn
Alvin, H. Ramesh, V. & Kumar, R. S. (2021). Bitcoin Price Prediction Using Machine Learning and Artificial Neural Network Model. Indian Journal Of Science And Technology, 2300-2308. https://doi.org/10.17485/IJST/v14i27.878
Aniruddha, D. Kumar, S. & Meheli, B. (2020). A gated recurrent unit approach to bitcoin price prediction. Journal of Risk and Financial Management, MDPI. https://arxiv.org/abs/1912.11166#:~:text=In%20today's%20era%20of%20big,predict%20Bitcoin%20price%20and%20volatility.
Bhavsar, S. & Gor, R. (2022). Comparison of Back propagation algorithms: Bidirectional GRU and Genetic Deep Neural Network for Churn Customer. International Organization of Scientific Research Journal of Computer Engineering (IOSR-JCE).
Bhavsar, S. & Gor, R. (2022). Predicting Restaurant Ratings using Back Propagation Algorithm. International Organization of Scientific Research journal of Applied Mathematics (IOSR-JM), 18(2), 5-9. https://iosrjournals.org/iosr-jm/papers/Vol18-issue2/Ser-2/C1802021014.pdf
Ethereum Races Clock to Collect Enough Coins for Big Upgrade. (2020). Retrieved from https://www.bloomberg.com/asia
Ghosh, M. & Gor, R. (2022). Ad-Campaign Analysis and Sales prediction using K-means Clustering and Random Forest Regressor. International Organization of Scientific Research Journal of Applied Mathematics, 18(2), 10-14. https://iosrjournals.org/iosr-jm/papers/Vol18-issue2/Ser-2/B1802020509.pdf
Ghosh, M. & Gor, R. (2022). Health Insurance Premium Prediction Using BlockChain Technology and Random Forest Resression Algorithm (In press). International Journal of Engineering Science Technologies (IJOEST). https://doi.org/10.29121/ijoest.v6.i3.2022.346
Ghosh, M. & Gor, R. (2022). Short Message service Classifier Application using Naive Bayes algorithm. IOSR Journal of Computer Engineering (IOSR-JCE), 24(3), 1-6.
Hochreiter, S. & Schmidhuber, J. (1997). Long Short Term Memory. Neural Computation, 1735-1780. https://doi.org/10.1162/neco.19126.96.36.1995
Ioannis, L. Kiriakidou, N. Stavroyiais, S. & Pitelas, P. (2021). An advanced CNN LSTM model for cryptocurrency forecasting. Electronics MDPI, 287 (1-16). https://www.mdpi.com/2079-9292/10/3/287
Pengfei, Y. & Yan, X. (2019). Stock price predictions based on deep neural networks. Neural computing and applications, 1609-1628. https://doi.org/10.1007/s00521-019-04212-x
Ping, H. J. Liu, J. & Jie, Y. (2021). Examaning the psychological state analysis relationship between bitcoin prices and COVID-19. Frontier in Psychology, 1-7. https://www.frontiersin.org/articles/10.3389/fpsyg.2021.647691/full
Rajpurohit, V. Bhavsar , S. & Gor, R. (2021). A comparision of GRU-based ETH price prediction. Proceeding of International Conference on Mathemaitcal Modelling and Simulation in Physical Sciences (MMSPS-2021), 424-431.
Salman, K. A. & Peter, A. (2019). Predictive Analytics in Cryptocurrency Using Neural networks: A Comparative Study. IJRTE, 7(6). https://www.researchgate.net/publication/336640118_Predictive_Analytics_in_Cryptocurrency_Using_Neural_networks_A_Comparative_Study
Shen, J. (2021). Short term stock market price trend prediction using comprehensive deep learning system. Journal of big data, 1-33. https://doi.org/10.1186/s40537-020-00333-6
Sheng, C. & Hongxiang, H. (2018). Stock Prediction Using Convolutional Neural Network. AIAAT Materials Science and Engineering, 435. https://doi.org/10.1088/1757-899X/435/1/012026
Yang, L. Zibin, Z. & Dai, H. N. (2020). Enhancing bitcoin price fluctuation predictionn using attentive LSTM and Embedding network. Applied sciences MDPI, 4872. https://doi.org/10.3390/app10144872
The Humanitarian Data Exchange (n.d.). Retrieved from data.humdata.org
Asian, C. W. (n.d.). shares end quarter in sombre mood, dollar on high Asian shares end quarter in sombre mood, dollar on high. https://www.investing.com/
impact-of-covid-19-on-cryptocurrencies. (2021). Retrieved from https://www.freepressjournal.in/business/impact-of-covid-19-on-cryptocurrencies
How to Cite
Copyright (c) 2022 Bhavsar Shachi, Ravi Gor
This work is licensed under a Creative Commons Attribution 4.0 International License.