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Can ChatGPT improve investment decisions? From a portfolio management perspective

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  • Ko, Hyungjin
  • Lee, Jaewook

Abstract

We examine ChatGPT, a prominent Large Language Model (LLM), in supporting portfolio management with a focus on asset selection and diversification through quantitative methods. We use ChatGPT to select assets from various asset classes and evaluate the diversification effect of its selections. Our results suggest that ChatGPT’s selections are statistically significantly better in diversity index than randomly selected assets. We also construct portfolios based on ChatGPT’s selections and find that they outperform portfolios built on randomly selected assets. Overall, our study contributes to a better understanding of the role of LLMs like ChatGPT as potential assistants for portfolio managers.

Suggested Citation

  • Ko, Hyungjin & Lee, Jaewook, 2024. "Can ChatGPT improve investment decisions? From a portfolio management perspective," Finance Research Letters, Elsevier, vol. 64(C).
    • Handle: RePEc:eee:finlet:v:64:y:2024:i:c:s154461232400463x
    DOI: 10.1016/j.frl.2024.105433
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    1. Pawe{l} Niszczota & Sami Abbas, 2023. "GPT has become financially literate: Insights from financial literacy tests of GPT and a preliminary test of how people use it as a source of advice," Papers 2309.00649, arXiv.org, revised Sep 2024.
    2. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    3. Seongwan Park & Seungju Lee & Yunyoung Lee & Hyungjin Ko & Bumho Son & Jaewook Lee & Huisu Jang, 2023. "Price co-movements in decentralized financial markets," Applied Economics Letters, Taylor & Francis Journals, vol. 30(21), pages 3075-3082, December.
    4. Oehler, Andreas & Horn, Matthias, 2024. "Does ChatGPT provide better advice than robo-advisors?," Finance Research Letters, Elsevier, vol. 60(C).
    5. Victor DeMiguel & Lorenzo Garlappi & Raman Uppal, 2009. "Optimal Versus Naive Diversification: How Inefficient is the 1-N Portfolio Strategy?," The Review of Financial Studies, Society for Financial Studies, vol. 22(5), pages 1915-1953, May.
    6. Ko, Hyungjin & Byun, Junyoung & Lee, Jaewook, 2023. "A privacy-preserving robo-advisory system with the Black-Litterman portfolio model: A new framework and insights into investor behavior," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 89(C).
    7. Ko, Hyungjin & Lee, Seungyun & Lee, Jaewook, 2024. "Sequence and longevity risks of South Korean retirees: Insights and potential remedies," Pacific-Basin Finance Journal, Elsevier, vol. 83(C).
    8. Ko, Hyungjin & Son, Bumho & Lee, Jaewook, 2024. "Portfolio insurance strategy in the cryptocurrency market," Research in International Business and Finance, Elsevier, vol. 67(PA).
    9. Barber, Brad M. & Odean, Terrance, 2013. "The Behavior of Individual Investors," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 1533-1570, Elsevier.
    10. Alejandro Lopez-Lira & Yuehua Tang, 2023. "Can ChatGPT Forecast Stock Price Movements? Return Predictability and Large Language Models," Papers 2304.07619, arXiv.org, revised Oct 2025.
    11. Niszczota, Paweł & Abbas, Sami, 2023. "GPT has become financially literate: Insights from financial literacy tests of GPT and a preliminary test of how people use it as a source of advice," Finance Research Letters, Elsevier, vol. 58(PA).
    12. Ko, Hyungjin & Son, Bumho & Lee, Jaewook, 2024. "A novel integration of the Fama–French and Black–Litterman models to enhance portfolio management," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 91(C).
    13. Dowling, Michael & Lucey, Brian, 2023. "ChatGPT for (Finance) research: The Bananarama Conjecture," Finance Research Letters, Elsevier, vol. 53(C).
    14. Shapira, Zur & Venezia, Itzhak, 2001. "Patterns of behavior of professionally managed and independent investors," Journal of Banking & Finance, Elsevier, vol. 25(8), pages 1573-1587, August.
    15. John H. Cochrane, 2014. "A Mean-Variance Benchmark for Intertemporal Portfolio Theory," Journal of Finance, American Finance Association, vol. 69(1), pages 1-49, February.
    16. Brad M. Barber & Terrance Odean, 2000. "Trading Is Hazardous to Your Wealth: The Common Stock Investment Performance of Individual Investors," Journal of Finance, American Finance Association, vol. 55(2), pages 773-806, April.
    17. Hyungjin Ko & Jaewook Lee & Junyoung Byun & Bumho Son & Saerom Park, 2019. "Loss-Driven Adversarial Ensemble Deep Learning for On-Line Time Series Analysis," Sustainability, MDPI, vol. 11(12), pages 1-24, June.
    18. Ko, Hyungjin & Son, Bumho & Lee, Yunyoung & Jang, Huisu & Lee, Jaewook, 2022. "The economic value of NFT: Evidence from a portfolio analysis using mean–variance framework," Finance Research Letters, Elsevier, vol. 47(PA).
    19. Oleksandr Romanko & Akhilesh Narayan & Roy H. Kwon, 2023. "ChatGPT-based Investment Portfolio Selection," Papers 2308.06260, arXiv.org.
    20. Avramov, Doron & Cheng, Si & Lioui, Abraham & Tarelli, Andrea, 2022. "Sustainable investing with ESG rating uncertainty," Journal of Financial Economics, Elsevier, vol. 145(2), pages 642-664.
    21. Pelster, Matthias & Val, Joel, 2024. "Can ChatGPT assist in picking stocks?," Finance Research Letters, Elsevier, vol. 59(C).
    22. Oleksandr Romanko & Akhilesh Narayan & Roy H. Kwon, 2023. "ChatGPT-Based Investment Portfolio Selection," SN Operations Research Forum, Springer, vol. 4(4), pages 1-27, December.
    23. Suleyman Basak & Georgy Chabakauri, 2010. "Dynamic Mean-Variance Asset Allocation," The Review of Financial Studies, Society for Financial Studies, vol. 23(8), pages 2970-3016, August.
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    Cited by:

    1. Dong, Mengming Michael & Stratopoulos, Theophanis C. & Wang, Victor Xiaoqi, 2024. "A scoping review of ChatGPT research in accounting and finance," International Journal of Accounting Information Systems, Elsevier, vol. 55(C).
    2. Minh Tam Tammy Schlosky & Serkan Karadas & Sterling Raskie, 2024. "ChatGPT, Help! I Am in Financial Trouble," JRFM, MDPI, vol. 17(6), pages 1-39, June.
    3. Gregory, Gadzinski & Vito, Liuzzi, 2024. "ChatGPT: A canary in the coal mine or a parrot in the echo chamber? Detecting fraud with LLM: The case of FTX," Finance Research Letters, Elsevier, vol. 70(C).
    4. Wang, Jying-Nan & Liu, Hung-Chun & Hsu, Yuan-Teng, 2025. "Do AI incidents and hazards matter for AI-themed cryptocurrency returns?," Finance Research Letters, Elsevier, vol. 74(C).
    5. Schneider, Constantin J. & Yilmaz, Yahya, 2025. "Stock portfolio selection based on risk appetite: Evidence from ChatGPT," Finance Research Letters, Elsevier, vol. 82(C).
    6. Liyuan Chen & Shuoling Liu & Jiangpeng Yan & Xiaoyu Wang & Henglin Liu & Chuang Li & Kecheng Jiao & Jixuan Ying & Yang Veronica Liu & Qiang Yang & Xiu Li, 2025. "Advancing Financial Engineering with Foundation Models: Progress, Applications, and Challenges," Papers 2507.18577, arXiv.org, revised Dec 2025.
    7. Jeong, Woojin & Park, Seongwan & Lee, Seungyun & Son, Bumho & Lee, Jaewook & Ko, Hyungjin, 2024. "Influence and predictive power of sentiment: Evidence from the lithium market," Finance Research Letters, Elsevier, vol. 68(C).
    8. Kevin He & Ran Shorrer & Mengjia Xia, 2025. "Human Misperception of Generative-AI Alignment:A Laboratory Experiment," PIER Working Paper Archive 25-019, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    9. Zhisheng Chen, 2025. "Revolutionizing finance with conversational AI: a focus on ChatGPT implementation and challenges," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 12(1), pages 1-11, December.
    10. Hoyoung Lee & Junhyuk Seo & Suhwan Park & Junhyeong Lee & Wonbin Ahn & Chanyeol Choi & Alejandro Lopez-Lira & Yongjae Lee, 2025. "Your AI, Not Your View: The Bias of LLMs in Investment Analysis," Papers 2507.20957, arXiv.org, revised Oct 2025.
    11. Hyungjin Ko & Jaewook Lee, 2025. "Portfolio Management Transformed: An Enhanced Black–Litterman Approach Integrating Asset Pricing Theory and Machine Learning," Computational Economics, Springer;Society for Computational Economics, vol. 66(5), pages 3841-3887, November.
    12. Chon, Sora & Kim, Jaehoon & Kim, Jaeho, 2025. "Multifaceted variability in LLM-driven stock recommendations," Finance Research Letters, Elsevier, vol. 86(PG).
    13. Jingru Jia & Zehua Yuan & Junhao Pan & Paul E. McNamara & Deming Chen, 2024. "Decision-Making Behavior Evaluation Framework for LLMs under Uncertain Context," Papers 2406.05972, arXiv.org, revised Oct 2024.
    14. Perlin, Marcelo S. & Foguesatto, Cristian R. & Müller, Fernanda M. & Righi, Marcelo B., 2025. "Can AI beat a naive portfolio? An experiment with anonymized data," Finance Research Letters, Elsevier, vol. 78(C).
    15. Yuqi Nie & Yaxuan Kong & Xiaowen Dong & John M. Mulvey & H. Vincent Poor & Qingsong Wen & Stefan Zohren, 2024. "A Survey of Large Language Models for Financial Applications: Progress, Prospects and Challenges," Papers 2406.11903, arXiv.org.
    16. Wang, Qishu, 2025. "Generative AI-assisted evaluation of ESG practices and information delays in ESG ratings," Finance Research Letters, Elsevier, vol. 74(C).
    17. Li, Degang & Bo, Lili, 2025. "The impact of health concerns on household financial asset allocation in the context of population aging," Finance Research Letters, Elsevier, vol. 85(PB).
    18. Xuewen Han & Neng Wang & Shangkun Che & Hongyang Yang & Kunpeng Zhang & Sean Xin Xu, 2024. "Enhancing Investment Analysis: Optimizing AI-Agent Collaboration in Financial Research," Papers 2411.04788, arXiv.org.
    19. Weilong Fu, 2025. "The New Quant: A Survey of Large Language Models in Financial Prediction and Trading," Papers 2510.05533, arXiv.org.
    20. Chiu, Ya-Ling & Gao, Xuechen & Liu, Hung-Chun & Zhai, Qiong, 2025. "Financial literacy of ChatGPT: Evidence through financial news," Finance Research Letters, Elsevier, vol. 78(C).
    21. Zhao, Yikai & Dai, Runyu & Nagayasu, Jun, 2025. "Generative AI: The transformative impact of ChatGPT on systemic financial risk in Chinese banks," Pacific-Basin Finance Journal, Elsevier, vol. 93(C).
    22. Tomasz Szopiński & Michał Buszko & Małgorzata Porada-Rochoń, 2026. "Acceptance of AI-based tools in consumer financial decision-making: An application of the extended technology acceptance model," PLOS ONE, Public Library of Science, vol. 21(3), pages 1-24, March.
    23. Lars Hornuf & David J. Streich & Niklas Töllich, 2025. "Making GenAI Smarter: Evidence from a Portfolio Allocation Experiment," CESifo Working Paper Series 11862, CESifo.
    24. Ali, Hassnian & Zafar, Muhammad Bilal & Aysan, Ahmet Faruk, 2025. "Generative AI in finance: Replicability, methodological contingencies, and future research directions," Finance Research Letters, Elsevier, vol. 86(PF).
    25. Jinseong Park & Hyungjin Ko & Jaewook Lee, 2025. "Modeling Asset Price Process: An Approach for Imaging Price Chart with Generative Diffusion Models," Computational Economics, Springer;Society for Computational Economics, vol. 66(1), pages 349-375, July.

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