Saurabh Parhad,
Shreyas Dumbre,
Priyanshu Agrawal,
Prasad Mete,
Vivek Mule,
- Student, RMD Sinhgad School of Engineering Maharashtra India
- Student, RMD Sinhgad School of Engineering Maharashtra India
- Student, RMD Sinhgad School of Engineering Maharashtra India
- Student, RMD Sinhgad School of Engineering Maharashtra India
- Student, RMD Sinhgad School of Engineering Maharashtra India
Abstract
This study looks at the main elements influencing daily price variations to improve our analysis and prediction of Bitcoin values. Our forecasting algorithm is based on comprehensive data that we have collected and analyzed over the last few years. Because the Random Forest algorithm provides more accurate forecasts than previous techniques, that is why we chose it. Predicting the price swings of cryptocurrencies, like Bitcoin, can be challenging due to market volatility, despite their increasing popularity as investments due to their decentralized nature and high return potential. Our method assists in addressing these challenges by providing investors, both novice and seasoned, with improved instruments to predict price fluctuations and make more informed investment choices.
Keywords: : Bitcoin, cryptocurrency, data analysis, random forest algorithm, machine learning
[This article belongs to Journal of Electronic Design Technology(joedt)]
References
- Shah and K. Zhang, “Bayesian regression and Bitcoin,” in 52nd Annual Allerton Conference on Communication, Control, and Computing (Allerton),2015 , pp. 409-415.
- Huisu Jang and Jaewook Lee, “An Empirical Study on Modelling and Prediction of Bitcoin Prices with Bayesian Neural Networks based on Blockchain Information,” in IEEE Early Access Articles, 2017, vol.99, pp. 1-1.
- Andrade de Oliveira, L. Enrique Zárate and M. deAzevedo Reis; C. NeriNobre, “The use of artificialneural networks in the analysis and prediction of stock prices,” in IEEE International Conference on Systems, Man, and Cybernetics, 2011, pp. 2151-2155.
- Daniela and A. BUTOI, “Data mining on Romanian stock market using neural networks for price prediction”.informatica Economica, 17,2013..
- Siddhi Velankar, SakshiValecha, Shreya Maji, “Bitcoin Price Prediction using Machine Learning,” 2018, ISBN 979-11-88428-01-4.
- XiangxiJiang,”Bitcoin Price Prediction Based on Deep Learning Methods”,Journal of Mathematical Finance, 2020, 10, 132-139.
- Yogeshwaran,Maninder Jeet Kaur,Piyush Maheshwari,“Project Based Learning: Predicting Bitcoin Prices using Deep Learning”, 978- 1-5386-9506-7/19/$31.00 ©2019 IEEE.
- Hellström T, Holmström K. The relevance of trends for predictions of stock returns. Intelligent Systems in Accounting, Finance & Management. 2000 Mar;9(1):23-34.
- Chen Z, Li C, Sun W. Bitcoin price prediction using machine learning: An approach to sample dimension engineering. Journal of Computational and Applied Mathematics. 2020 Feb 1;365:112395.
Journal of Electronic Design Technology
Volume | 15 |
Issue | 02 |
Received | July 26, 2024 |
Accepted | July 31, 2024 |
Published | August 16, 2024 |