DQN Trading Bot

⚠️ This project is undergoing transition from a sentiment-based trading bot to a DQN-based trading bot. This README has not been updated yet to reflect this change.

Table of Contents

• Features
• Installation
• Usage
• Files
• License

Features

• Alpaca Integration: Uses the Alpaca API to place buy/sell orders and manage positions.
• Sentiment Analysis: Leverages the FinBERT model (a pre-trained BERT model) to predict the sentiment of financial news headlines.
• Backtesting: Includes the ability to backtest the strategy with historical data using Yahoo Finance.
• Risk Management: Implements stop-loss and take-profit mechanisms for automated trade execution.

Installation

1. Clone the repository:

git clone https://github.com/yourusername/sentiment-trading-bot.git
cd sentiment-trading-bot

2. Install the required packages:

pip install -r requirements.txt

3. Set up environment variables: Create a .env file in the root directory and add your Alpaca API credentials:

API_KEY=your_alpaca_api_key
API_SECRET=your_alpaca_api_secret
BASE_URL=https://paper-api.alpaca.markets

Usage

1. Run the trading bot:

python bot.py

2. Backtest the strategy: The backtesting is already included in the bot.py script. It uses Yahoo Finance data to backtest the strategy from January 1, 2020, to January 1, 2025.

Files

• bot.py: Contains the main trading bot implementation.
• sentiment.py: Contains the sentiment analysis function using the FinBERT model.

License

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