This project aims to forecast stock prices by leveraging market news sentiment and historical stock data. It collects news articles about stocks, analyzes their sentiment, and trains predictive models to make informed forecasts.
- Fetches stock news from APIs
- Calculates sentiment scores for news articles
- Collects and processes historical stock data
- Trains models (including LSTM) on past data and sentiment
- Makes stock price predictions based on combined data
- Python dependencies listed in
requirements.txt - Alpha Vantage API key (for stock data)
- Finnhub API key (for news data)
- Clone this repository.
- Install dependencies:
pip install -r requirements.txt
- Obtain API keys for Alpha Vantage and Finnhub, and configure them as needed in the code.
Run main.py with ticker as argument
- Outputs and results will be added later.
- Aditya Gupta