The Concept

The Agentic AI Stock Flywheel is a framework that treats market analysis as a continuous, closed-loop system. Instead of generating a single signal and acting on it, the flywheel approach creates multiple AI agents that each specialize in a different aspect of market analysis — fundamental, technical, sentiment, and macro — and feeds their outputs back into the system.

Each agent operates autonomously but shares its findings with the others. A fundamental agent might flag an undervalued stock based on MAVI scores, which triggers a sentiment agent to scan news and social media for confirmation or contradiction. If the signals align, an execution agent places the trade and later reports back on performance, completing the flywheel.

Key Components

• 🔄 Data Pipeline: Real-time ingestion of price data, financial statements, news feeds, and alternative data sources.
• 🧠 Multi-Agent Analysis: Specialized LLM-based agents for fundamental, technical, sentiment, and macro analysis.
• ⚡ Signal Aggregation: Weighted consensus mechanism that combines agent outputs into actionable trade signals.
• 📊 Performance Feedback: Each trade outcome feeds back to improve agent models through reinforcement learning.
• 🔁 The Flywheel Effect: Better analysis → better trades → more data → better analysis.