crisp-journey

Real-Time Financial News Analysis and Market Trend Prediction

Project Description

The goal of this project is to build a system that analyzes real-time financial news and predicts market trends. The system will use a large language model to perform sentiment analysis on financial news articles and a basic machine learning model to predict the stock price's future direction, either 'bullish or bearish.

Data Sources

• Historical stock price data: This data will be collected from https://finnhub.io/.
• Financial news articles: These will be collected from https://finnhub.io/.

Project Structure

/project-directory |-- /data |-- /notebooks |-- /src |-- /docs |-- README.md |-- requirements.txt

• data: Directory to store data files.
• notebooks: Directory for Jupyter notebooks.
• src: Directory for Python scripts and source code.
• docs: Directory for documentation.

Installation

1. Clone this repository to your local machine.
2. Install the required Python packages by running pip install -r requirements.txt in your terminal.
3. Install a SQL database like SQLite or MySQL.

Usage

1. Collect the historical stock price data and financial news articles and store them in the data directory.
2. Perform data preprocessing and sentiment analysis using the notebooks in the notebooks directory.
3. Train the machine learning model using the notebooks in the notebooks directory.
4. Evaluate the model's performance and fine-tune it if necessary.
5. Deploy the model in a real-time environment and continuously monitor its performance.

Contributing

Please feel free to fork this repository, make changes, and submit pull requests. Any contributions, no matter how small, are greatly appreciated.

License

This project is licensed under the MIT License. See the LICENSE file for more details.

Contact

If you have any questions or feedback, please feel free to contact me at [email protected].