IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v58y2023ipds1544612323009522.html
   My bibliography  Save this article

What if ChatGPT were a quant asset manager

Author

Listed:
  • Kim, Jang Ho

Abstract

Even though large language models such as ChatGPT are not specifically trained for analyzing asset returns or recommending stocks, it may still provide additional insight into making investment decisions. In this study, we propose a quantitative investment approach that incorporates recommendations from ChatGPT. Based on ChatGPT's general understanding of economy and financial market movements, we ask ChatGPT to recommend asset classes under various economic conditions. Our empirical results show that asset class recommendations based on economic indicators of ChatGPT can improve portfolio efficiency.

Suggested Citation

  • Kim, Jang Ho, 2023. "What if ChatGPT were a quant asset manager," Finance Research Letters, Elsevier, vol. 58(PD).
  • Handle: RePEc:eee:finlet:v:58:y:2023:i:pd:s1544612323009522
    DOI: 10.1016/j.frl.2023.104580
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1544612323009522
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.frl.2023.104580?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Saggu, Aman & Ante, Lennart, 2023. "The influence of ChatGPT on artificial intelligence related crypto assets: Evidence from a synthetic control analysis," Finance Research Letters, Elsevier, vol. 55(PB).
    2. Dowling, Michael & Lucey, Brian, 2023. "ChatGPT for (Finance) research: The Bananarama Conjecture," Finance Research Letters, Elsevier, vol. 53(C).
    3. Oleksandr Romanko & Akhilesh Narayan & Roy H. Kwon, 2023. "ChatGPT-based Investment Portfolio Selection," Papers 2308.06260, arXiv.org.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bonaparte, Yosef, 2024. "Artificial Intelligence in Finance: Valuations and Opportunities," Finance Research Letters, Elsevier, vol. 60(C).
    2. Ko, Hyungjin & Lee, Jaewook, 2024. "Can ChatGPT improve investment decisions? From a portfolio management perspective," Finance Research Letters, Elsevier, vol. 64(C).
    3. Wahyono, Budi & Rapih, Subroto & Boungou, Whelsy, 2023. "Unleashing the wordsmith: Analysing the stock market reactions to the launch of ChatGPT in the US Education sector," Finance Research Letters, Elsevier, vol. 58(PC).
    4. Smales, Lee A., 2023. "Classification of RBA monetary policy announcements using ChatGPT," Finance Research Letters, Elsevier, vol. 58(PC).
    5. Hassnian Ali & Ahmet Faruk Aysan, 2023. "What will ChatGPT revolutionize in the financial industry?," Modern Finance, Modern Finance Institute, vol. 1(1), pages 116-129.
    6. Lennart Ante & Ender Demir, 2024. "The ChatGPT effect on AI-themed cryptocurrencies," Economics and Business Letters, Oviedo University Press, vol. 13(1), pages 29-38.
    7. Alonso-Robisco, Andres & Carbó, José Manuel, 2023. "Analysis of CBDC narrative by central banks using large language models," Finance Research Letters, Elsevier, vol. 58(PC).
    8. Christian Fieberg & Lars Hornuf & David J. Streich, 2023. "Using GPT-4 for Financial Advice," CESifo Working Paper Series 10529, CESifo.
    9. 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).
    10. Li Xian Liu & Zhiyue Sun & Kunpeng Xu & Chao Chen, 2024. "AI-Driven Financial Analysis: Exploring ChatGPT’s Capabilities and Challenges," IJFS, MDPI, vol. 12(3), pages 1-35, June.
    11. 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).
    12. 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.
    13. Ardekani, Aref Mahdavi & Bertz, Julie & Bryce, Cormac & Dowling, Michael & Long, Suwan(Cheng), 2024. "FinSentGPT: A universal financial sentiment engine?," International Review of Financial Analysis, Elsevier, vol. 94(C).
    14. Mohammad S. Jalali & Ali Akhavan, 2024. "Integrating AI language models in qualitative research: Replicating interview data analysis with ChatGPT," System Dynamics Review, System Dynamics Society, vol. 40(3), July.
    15. Song, Piaopeng & Lu, Hanglin & Zhang, Yongjie, 2024. "Unveiling tone manipulation in MD&A: Evidence from ChatGPT experiments," Finance Research Letters, Elsevier, vol. 67(PA).
    16. Paraná, Edemilson, 2024. "AI as financial infrastructure?," SocArXiv ub92z, Center for Open Science.
    17. Yuhui Jing & Haoming Wang & Xiaojiao Chen & Chengliang Wang, 2024. "What factors will affect the effectiveness of using ChatGPT to solve programming problems? A quasi-experimental study," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-12, December.
    18. Jiang, Jiaqi & Zhang, Zhipeng & Cheng, Gongpin, 2024. "Corporate violations, traditional media and stock returns: Evidence from Chinese listed companies," Finance Research Letters, Elsevier, vol. 69(PA).
    19. Ali Akhavan & Mohammad S. Jalali, 2024. "Generative AI and simulation modeling: how should you (not) use large language models like ChatGPT," System Dynamics Review, System Dynamics Society, vol. 40(3), July.
    20. Feng, Jianghong & Ning, Yu & Wang, Zhaohua & Li, Guo & Xiu Xu, Su, 2024. "ChatGPT-enabled two-stage auctions for electric vehicle battery recycling," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 183(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:finlet:v:58:y:2023:i:pd:s1544612323009522. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/frl .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.