Autonomous, multi-agent quantitative trading system combining evolutionary strategy optimization, real-time risk controls, LLM sentiment scoring, and distributed swarm processing.
Genetic optimization algorithm (evolution_engine.py) running continuous strategy mutation, crossover, and fitness evaluations.
Natural Language Processing agent (sentiment_agent.py) powered by Amazon Bedrock for real-time market sentiment evaluation.
Distributed event consumer (swarm_consumer.py) coordinating asynchronous task queues, signal aggregation, and market streaming data (data_producer.py).
Automated risk manager (risk_engine.py) executing real-time position sizing, maximum drawdown monitoring, and exposure limits.
Streamlit monitoring dashboard (dashboard.py) integrated with a high-precision historical simulation engine (backtest.py).
Full microservice orchestration via Docker & Docker Compose with structured telemetry storage (db_manager.py).