Kraken Meta-Agent Trading System

This project introduces a regime-aware autonomous trading architecture that shifts the focus from predictive modeling to adaptive portfolio allocation. Instead of attempting to forecast price movements, the system emphasizes robustness through dynamic regime detection and controlled exposure. At its core, the architecture separates the execution layer from the model evolution layer. The execution layer operates as a deterministic trading agent, handling market data ingestion, signal processing, risk constraints, and order execution via Kraken integration. It focuses strictly on allocation and exposure management rather than prediction. Above it, a meta-agent system continuously refines and evolves trading models using feedback from market performance. This recursive loop enables continuous improvement without destabilizing live execution. The system integrates regime scoring based on momentum, volatility, drawdown, relative strength, and persistence, allowing capital allocation to adapt across changing market conditions. Portfolio construction follows a hierarchical structure: capital is first allocated across asset classes using regime scores, then distributed within each class using model-driven signals, including GRU-based forecasts and technical indicators. The result is not a conventional trading bot, but a self-improving financial system designed for stability, adaptability, and long-term survival in complex markets.