A First Look at Financial Data Analysis Using ChatGPT-4o

Wen-Hsiu (Julia) Chou, Zifeng Feng (), Bingxin Li and Feng Liu
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Wen-Hsiu (Julia) Chou: College of Business, Florida International University, 11200 SW 8th St., Miami, FL 33199, USA
Zifeng Feng: College of Business Administration, The University of Texas at El Paso, 500 W. University Ave., El Paso, TX 79968, USA
Bingxin Li: John Chambers College of Business and Economics, West Virginia University, 83 Beechurst Avenue, Morgantown, WV 26505, USA
Feng Liu: College of Business Administration, The University of Texas at El Paso, 500 W. University Ave., El Paso, TX 79968, USA

JRFM, 2025, vol. 18, issue 2, 1-35

Abstract: OpenAI’s new flagship model, ChatGPT-4o, released on 13 May 2024, offers enhanced natural language understanding and more coherent responses. This paper investigates ChatGPT-4o’s capabilities in financial data analysis, including zero-shot prompting, time series analysis, risk and return analysis, and ARMA-GARCH estimation. ChatGPT-4o’s performance is generally comparable to traditional statistical software like Stata, though some errors and discrepancies arise due to differences in implementation. Despite these issues, our findings indicate that ChatGPT-4o has significant potential for real-world financial analysis. Integrating ChatGPT-4o into financial research and practice may lead to more efficient data processing, improved analytical capabilities, and better-informed investment decisions.

Keywords: ChatGPT; large language models; artificial intelligence (AI); generative AI (GenAI); finance research; financial analysis; academia; data analysis; stock return (search for similar items in EconPapers)
JEL-codes: C E F2 F3 G (search for similar items in EconPapers)
Date: 2025
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