This project is a hands-on implementation of a real-time algorithmic trading system that processes market data and news sentiment to make automated trading decisions. It integrates Apache Flink for stream processing, Redpanda for data streaming, and the Alpaca API for market data and trade execution, with sentiment analysis driving the strategy.
Technologies Used
- Apache Flink: Real-time stream processing.
- Redpanda: High-performance data brokering.
- Alpaca API: Market data and trading operations.
- NLTK (VADER): News sentiment analysis.
- Docker: Service orchestration.
- Python: Core scripting.
- SQL: Flink data processing and transformation
How It Works
- Data Ingestion: Python scripts fetch news and stock prices from Alpaca, analyze sentiment, and stream data to Redpanda.
- Stream Processing: Flink processes the data, combining sentiment scores with price trends to generate trading signals.
- Trade Execution: Signals trigger Slack notifications and automated trades via Alpaca.
Key Acheivements
Successfully built a system that processes live data and executes trades based on a custom strategy, demonstrating real-time data engineering in action.
Link: Read the full article on Medium
Code: https://github.com/shj37/Algo-Trading-Sentiment-Analysis-Redpanda-Flink
