This project leverages the Prophet time series forecasting model to predict Bitcoin prices, incorporating five years of comprehensive market data. The focus is on critical market dynamics such as volatility, market cycles, investor sentiment, and particularly the 2024 Bitcoin halving event—a pivotal occurrence historically influencing Bitcoin's value. By analyzing data around previous halvings, the model aims to uncover trends crucial for forecasting future Bitcoin prices.
- Prophet Forecasting Model: Utilizes Facebook's Prophet model for its intuitive and robust time series forecasting capabilities.
- Halving Events Analysis: Examines the impact of Bitcoin halving events on market price dynamics.
- Comprehensive Data Analysis: Includes an analysis of volatility, market cycles, and investor sentiment to enhance forecasting accuracy.
- Visualization: Offers clear visualizations for comparing actual prices against forecasted scenarios.
The methodology employs the Prophet model to analyze historical Bitcoin data. Special attention is given to periods surrounding Bitcoin halving events to enhance the accuracy of future price predictions.
- Educational Purpose Only: This research is solely for educational purposes and constitutes a self-study project.
- Not Financial Advice: Predictions generated by this code are for educational use only and should not be considered financial or investment advice.
- No Responsibility: The author and contributors to this repository assume no responsibility for any financial losses incurred.
- Accuracy Not Guaranteed: The predictive performance of these models cannot be guaranteed.
- Independent research: Users are encouraged to research and consult with professionals.
- Compliance with Laws: Users must ensure compliance with all applicable laws and regulations in their jurisdiction.
- Python 3.11
- Git
First, create and activate a virtual environment:
python -m venv .venv # Create a virtual environment
source .venv/bin/activate # Activate on macOS and Linux
.venv\Scripts\activate # Activate on Windows
Install the required dependencies:
pip install -r requirements.txt # Install Python dependencies
npm install dukascopy-node --save # Install Node.js dependencies
chmod +x data-download.sh
./data-download.sh
- Use PowerShell or Git Bash for shell commands.
- Ensure Docker Desktop for Windows is set to Linux containers.
- Python commands may require using
py
instead ofpython
orpython3
.
To get started, clone the repository:
git clone git@github.com:SMARTSHEEP-IO/bitcoin-price-forecasting-using-prophet.git
Execute the main.py
script to start the data processing and model training/prediction process:
python main.py
- Farsi Channel: Dr. Samizadeh
- English Channel: Programming in 10 Minutes
Contributions to improve the project are welcome. Please adhere to standard open-source contribution guidelines.
If this project aids in your research or any other project, kindly cite it as follows:
@misc{Samizadeh2024BitcoinProphet,
author = {Samizadeh, Iman},
title = {{Enhanced Bitcoin Price Forecasting for 2024 Halving Using Prophet}},
year = {2024},
howpublished = {\url{https://github.com/SMARTSHEEP-IO/bitcoin-price-forecasting-using-prophet}}
}
Credit:
- https://github.com/Leo4815162342/dukascopy-node
- Prophet Documentation: https://facebook.github.io/prophet/
Keywords: Bitcoin, Halving, Prediction, Volatility, Growth, ATH, Cryptocurrency, Analysis, Financial Modeling, Prophet