IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2404.00012.html
   My bibliography  Save this paper

Stress index strategy enhanced with financial news sentiment analysis for the equity markets

Author

Listed:
  • Baptiste Lefort
  • Eric Benhamou
  • Jean-Jacques Ohana
  • David Saltiel
  • Beatrice Guez
  • Thomas Jacquot

Abstract

This paper introduces a new risk-on risk-off strategy for the stock market, which combines a financial stress indicator with a sentiment analysis done by ChatGPT reading and interpreting Bloomberg daily market summaries. Forecasts of market stress derived from volatility and credit spreads are enhanced when combined with the financial news sentiment derived from GPT-4. As a result, the strategy shows improved performance, evidenced by higher Sharpe ratio and reduced maximum drawdowns. The improved performance is consistent across the NASDAQ, the S&P 500 and the six major equity markets, indicating that the method generalises across equities markets.

Suggested Citation

  • Baptiste Lefort & Eric Benhamou & Jean-Jacques Ohana & David Saltiel & Beatrice Guez & Thomas Jacquot, 2024. "Stress index strategy enhanced with financial news sentiment analysis for the equity markets," Papers 2404.00012, arXiv.org.
  • Handle: RePEc:arx:papers:2404.00012
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2404.00012
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Alejandro Lopez-Lira & Yuehua Tang, 2023. "Can ChatGPT Forecast Stock Price Movements? Return Predictability and Large Language Models," Papers 2304.07619, arXiv.org, revised Sep 2023.
    2. Anton Korinek, 2023. "Language Models and Cognitive Automation for Economic Research," NBER Working Papers 30957, National Bureau of Economic Research, Inc.
    3. Paul C. Tetlock, 2007. "Giving Content to Investor Sentiment: The Role of Media in the Stock Market," Journal of Finance, American Finance Association, vol. 62(3), pages 1139-1168, June.
    4. W. Brooke Elliott & Stephanie M. Grant & Frank D. Hodge, 2018. "Negative News and Investor Trust: The Role of $Firm and #CEO Twitter Use," Journal of Accounting Research, Wiley Blackwell, vol. 56(5), pages 1483-1519, December.
    5. Tim Loughran & Bill Mcdonald, 2011. "When Is a Liability Not a Liability? Textual Analysis, Dictionaries, and 10‐Ks," Journal of Finance, American Finance Association, vol. 66(1), pages 35-65, February.
    6. Brad M. Barber & Terrance Odean, 2008. "All That Glitters: The Effect of Attention and News on the Buying Behavior of Individual and Institutional Investors," The Review of Financial Studies, Society for Financial Studies, vol. 21(2), pages 785-818, April.
    7. Ikizlerli, Deniz & Holmes, Phil & Anderson, Keith, 2019. "The response of different investor types to macroeconomic news," Journal of Multinational Financial Management, Elsevier, vol. 50(C), pages 13-28.
    8. Cheol-Won Yang, 2023. "Investment strategy via analyst report text mining," Journal of Derivatives and Quantitative Studies: 선물연구, Emerald Group Publishing Limited, vol. 31(2), pages 98-120, March.
    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. Ahmed, Yousry & Elshandidy, Tamer, 2016. "The effect of bidder conservatism on M&A decisions: Text-based evidence from US 10-K filings," International Review of Financial Analysis, Elsevier, vol. 46(C), pages 176-190.
    2. Ferdinand Graf, 2011. "Mechanically Extracted Company Signals and their Impact on Stock and Credit Markets," Working Paper Series of the Department of Economics, University of Konstanz 2011-18, Department of Economics, University of Konstanz.
    3. Ahmad, Khurshid & Han, JingGuang & Hutson, Elaine & Kearney, Colm & Liu, Sha, 2016. "Media-expressed negative tone and firm-level stock returns," Journal of Corporate Finance, Elsevier, vol. 37(C), pages 152-172.
    4. Bannier, Christina E. & Pauls, Thomas & Walter, Andreas, 2017. "CEO-speeches and stock returns," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168192, Verein für Socialpolitik / German Economic Association.
    5. Frijns, Bart & Huynh, Thanh D., 2018. "Herding in analysts’ recommendations: The role of media," Journal of Banking & Finance, Elsevier, vol. 91(C), pages 1-18.
    6. Alejandro Bernales & Marcela Valenzuela & Ilknur Zer, 2023. "Effects of Information Overload on Financial Markets: How Much Is Too Much?," International Finance Discussion Papers 1372, Board of Governors of the Federal Reserve System (U.S.).
    7. Jūra Liaukonytė & Alminas Žaldokas, 2022. "Background Noise? TV Advertising Affects Real-Time Investor Behavior," Management Science, INFORMS, vol. 68(4), pages 2465-2484, April.
    8. Tsai, Feng-Tse & Lu, Hsin-Min & Hung, Mao-Wei, 2016. "The impact of news articles and corporate disclosure on credit risk valuation," Journal of Banking & Finance, Elsevier, vol. 68(C), pages 100-116.
    9. Wu, Yanling & Tian, Gary Gang, 2021. "Public relations expenditure, media tone, and regulatory decisions," Journal of Corporate Finance, Elsevier, vol. 66(C).
    10. Oleg Chuprinin & Massimo Massa & Bastian von Beschwitz, 2015. "Why Do Short Sellers Like Qualitative News?," International Finance Discussion Papers 1149, Board of Governors of the Federal Reserve System (U.S.).
    11. Saadon, Yossi & Schreiber, Ben Z., 2023. "Newspapers tone and the overnight-intraday stock return anomaly," Journal of Financial Markets, Elsevier, vol. 65(C).
    12. Du, Hanyu & Hao, Jing & He, Feng & Xi, Wenze, 2022. "Media sentiment and cross-sectional stock returns in the Chinese stock market," Research in International Business and Finance, Elsevier, vol. 60(C).
    13. Campbell, Gareth & Turner, John D. & Walker, Clive B., 2012. "The role of the media in a bubble," Explorations in Economic History, Elsevier, vol. 49(4), pages 461-481.
    14. Zhi Da & Borja Larrain & Clemens Sialm & José Tessada, 2016. "Coordinated Noise Trading: Evidence from Pension Fund Reallocations," NBER Working Papers 22161, National Bureau of Economic Research, Inc.
    15. Price, S. McKay & Doran, James S. & Peterson, David R. & Bliss, Barbara A., 2012. "Earnings conference calls and stock returns: The incremental informativeness of textual tone," Journal of Banking & Finance, Elsevier, vol. 36(4), pages 992-1011.
    16. Zhang, Xiaotao & Li, Guoran & Li, Yishuo & Zou, Gaofeng & Wu, Ji George, 2023. "Which is more important in stock market forecasting: Attention or sentiment?," International Review of Financial Analysis, Elsevier, vol. 89(C).
    17. Aman, Hiroyuki & Moriyasu, Hiroshi, 2022. "Effect of corporate disclosure and press media on market liquidity: Evidence from Japan," International Review of Financial Analysis, Elsevier, vol. 82(C).
    18. Brière, Marie & Huynh, Karen & Laudy, Olav & Pouget, Sébastien, 2023. "What do we Learn from a Machine Understanding: News Content? Stock Market Reaction to News," TSE Working Papers 23-1401, Toulouse School of Economics (TSE).
    19. Yen-Ju Hsu & Yang-Cheng Lu & J. Jimmy Yang, 2021. "News sentiment and stock market volatility," Review of Quantitative Finance and Accounting, Springer, vol. 57(3), pages 1093-1122, October.
    20. Aakriti Mathur & Rajeswari Sengupta & Bhanu Pratap, 2022. "Saved by the bell? Equity market responses to surprise Covid-19 lockdowns and central bank interventions," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2022-001, Indira Gandhi Institute of Development Research, Mumbai, India.

    More about this item

    Statistics

    Access and download statistics

    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:arx:papers:2404.00012. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.