Can Large Language Models Beat Wall Street? Unveiling the Potential of AI in Stock Selection

• URL: http://arxiv.org/abs/2401.03737v2
• Date: Thu, 4 Apr 2024 13:18:55 GMT
• Title: Can Large Language Models Beat Wall Street? Unveiling the Potential of AI in Stock Selection
• Authors: Georgios Fatouros, Konstantinos Metaxas, John Soldatos, Dimosthenis Kyriazis,
• Abstract summary: This paper introduces MarketSenseAI, an innovative framework leveraging GPT-4's advanced reasoning for selecting stocks in financial markets. MarketSenseAI analyzes diverse data sources, including market trends, news, fundamentals, and macroeconomic factors, to emulate expert investment decision-making. Our findings highlight the transformative potential of Large Language Models in financial decision-making.
• Score: 0.07499722271664146
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: This paper introduces MarketSenseAI, an innovative framework leveraging GPT-4's advanced reasoning for selecting stocks in financial markets. By integrating Chain of Thought and In-Context Learning, MarketSenseAI analyzes diverse data sources, including market trends, news, fundamentals, and macroeconomic factors, to emulate expert investment decision-making. The development, implementation, and validation of the framework are elaborately discussed, underscoring its capability to generate actionable and interpretable investment signals. A notable feature of this work is employing GPT-4 both as a predictive mechanism and signal evaluator, revealing the significant impact of the AI-generated explanations on signal accuracy, reliability and acceptance. Through empirical testing on the competitive S&P 100 stocks over a 15-month period, MarketSenseAI demonstrated exceptional performance, delivering excess alpha of 10% to 30% and achieving a cumulative return of up to 72% over the period, while maintaining a risk profile comparable to the broader market. Our findings highlight the transformative potential of Large Language Models in financial decision-making, marking a significant leap in integrating generative AI into financial analytics and investment strategies.

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