MarketSenseAI 2.0 advances stock analysis by deploying a modular framework of LLM agents and advanced Retrieval-Augmented Generation to integrate diverse financial data, achieving consistent outperformance with 8.0-18.9% alpha and superior risk-adjusted returns on S&P 100/500 stocks. The system provides transparent investment rationales and overcomes common LLM limitations in financial applications.
This research introduces MarketSenseAI, a GPT-4-powered framework that integrates multi-modal financial data for advanced stock selection. The system consistently outperformed S&P 100 benchmarks over 15 months, with strategies achieving up to 71.64% total return after accounting for transaction costs, and it provides explainable investment signals.
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