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

arXiv:2401.03737v2 Announce Type: replace-cross
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 …

abstract advanced arxiv chain of thought context cs.ai cs.ce cs.cl cs.lg data data sources diverse financial financial markets framework fundamentals gpt gpt-4 in-context learning language language models large language large language models market markets paper q-fin.cp reasoning stock stocks street thought trends type wall street