IDEAS home Printed from https://ideas.repec.org/a/eee/pacfin/v96y2026ics0927538x26000089.html

Hedging financial turbulence risk with textual analysis

Author

Listed:
  • Liu, Qingfu
  • Tse, Yiuman
  • Wang, Chuanjie
  • Yang, Jiaer

Abstract

Financial turbulence poses substantial challenges to risk management and investment decision-making, particularly in emerging markets. This study constructs a novel Chinese Financial Turbulence Index (FTI) using a dictionary-based method augmented by generative artificial intelligence, drawing from a corpus of over 3.6 million financial news articles spanning 2012 to 2023. The FTI exhibits strong responsiveness to macroeconomic conditions and market uncertainty, and significantly predicts negative market returns. To mitigate risks associated with financial turbulence, we develop a hedging framework that integrates scaled principal component analysis (sPCA) with a portfolio-mimicking strategy. The resulting hedging portfolio, which is based on firm-level financial resilience characteristics and complemented by non-equity assets, effectively offsets turbulence-related risks. The FTI and the proposed hedging approach offer timely and practical tools for monitoring and managing financial turbulence.

Suggested Citation

  • Liu, Qingfu & Tse, Yiuman & Wang, Chuanjie & Yang, Jiaer, 2026. "Hedging financial turbulence risk with textual analysis," Pacific-Basin Finance Journal, Elsevier, vol. 96(C).
    • Handle: RePEc:eee:pacfin:v:96:y:2026:i:c:s0927538x26000089
    DOI: 10.1016/j.pacfin.2026.103062
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0927538X26000089
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.pacfin.2026.103062?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

    for a different version of it.

    More about this item

    Keywords

    ;
    ;
    ;

    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:eee:pacfin:v:96:y:2026:i:c:s0927538x26000089. 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.

    We have no bibliographic references for this item. You can help adding them by using 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/pacfin .

    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.