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)]
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Journal of Electronic Design Technology
| Volume | 15 |
| Issue | 02 |
| Received | July 26, 2024 |
| Accepted | July 31, 2024 |
| Published | August 16, 2024 |