IDEAS home Printed from https://ideas.repec.org/p/zbw/esprep/335572.html

Using Natural Language Processing to Identify Sentiment of Green Investors

Author

Listed:
  • Janda, Karel
  • Rozsahegyi, Marketa
  • Quang Van Tran
  • Zhang, Binyi

Abstract

This paper investigates the role of investor sentiment in the pricing and volatility dynamics of green bond exchange-traded funds (ETFs). The paper combines verbal description with a literature review, and it does not engage in actual data-based research analysis. While the literature on sentiment finance and ESG investing has expanded rapidly, empirical evidence focusing on fixed-income ESG instruments remains limited. We address this gap by employing modern natural language processing (NLP) techniques to construct sentiment indicators derived from news coverage and sustainability-related textual information. These indicators may be used to examine their impact on returns and volatility of selected green bond ETFs. By combining behavioural finance insights with state-of-the-art NLP methods, the paper contributes to sustainable finance research and highlights the informational role of textual data in green financial markets.

Suggested Citation

  • Janda, Karel & Rozsahegyi, Marketa & Quang Van Tran & Zhang, Binyi, 2025. "Using Natural Language Processing to Identify Sentiment of Green Investors," EconStor Preprints 335572, ZBW - Leibniz Information Centre for Economics.
    • Handle: RePEc:zbw:esprep:335572
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/335572/1/Des01.pdf
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    ;
    ;
    ;

    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:zbw:esprep:335572. 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: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/zbwkide.html .

    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.