AlphaAgents for Stock Evaluation
Personal learning project to implement the debate-driven multi-agent framework from BlackRock’s Aug 2025 paper for stock evaluation.
Aug 2025 – Present•Systems Engineer
Highlights
- Implemented domain-specific agents that emit structured reports with reasoning, metrics, and confidence scoring.
- Built a debate engine that streams multi-round critiques over SSE while logging every turn to reasoning_trace.jsonl.
- Developed a coordinator module that applies majority voting and deterministic tie-breakers to synthesize consensus.
- Visualized cumulative returns, rolling Sharpe, and drawdowns with Matplotlib dashboards backed by mock backtests.
Outcomes
- Delivered an explainable baseline mirroring BlackRock’s research and ready for reinforcement-learning extensions.
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I'm exploring AI agents, market-tech systems, and music-driven interfaces. Message me on LinkedIn if you want to collaborate or chat about tech.
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