IDEAS home Printed from https://ideas.repec.org/a/gam/jjrfmx/v16y2023i8p376-d1218076.html

Aggregate News Sentiment and Stock Market Returns in India

Author

Listed:
  • Sushant Chari

    (Saraswat Education Society’s Sridora Caculo College of Commerce & Management Studies, Mapusa 403507, Goa, India)

  • Purva Hegde Desai

    (Goa Business School, Goa University, Panaji 403206, Goa, India)

  • Nilesh Borde

    (Goa Business School, Goa University, Panaji 403206, Goa, India)

  • Babu George

    (School of Business, Alcorn State University, Lorman, MS 39096, USA)

Abstract

This paper contributes to the advancement of noise trader theory by examining the connection between aggregate news sentiment and stock market returns during days of significant stock market movement. In contrast to previous studies that solely focused on company-specific news sentiment, this research explores the impact of aggregate news sentiment. To draw conclusions, GARCH modeling, regression analysis, and dictionary-based sentiment analysis are employed. The findings, based on data from India, reveal that aggregate news sentiment has a short-lived influence, with notable effects stemming from the business and politics categories.

Suggested Citation

  • Sushant Chari & Purva Hegde Desai & Nilesh Borde & Babu George, 2023. "Aggregate News Sentiment and Stock Market Returns in India," JRFM, MDPI, vol. 16(8), pages 1-18, August.
    • Handle: RePEc:gam:jjrfmx:v:16:y:2023:i:8:p:376-:d:1218076
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1911-8074/16/8/376/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1911-8074/16/8/376/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mr. Sunil Sharma & Sushil Bikhchandani, 2000. "Herd Behavior in Financial Markets: A Review," IMF Working Papers 2000/048, International Monetary Fund.
    2. Wataru Souma & Irena Vodenska & Hideaki Aoyama, 2019. "Enhanced news sentiment analysis using deep learning methods," Journal of Computational Social Science, Springer, vol. 2(1), pages 33-46, January.
    3. Peggy M. Lee, 1997. "A comparative analysis of layoff announcements and stock price reactions in the United States and Japan," Strategic Management Journal, Wiley Blackwell, vol. 18(11), pages 879-894, December.
    4. Huina Mao & Scott Counts & Johan Bollen, 2011. "Predicting Financial Markets: Comparing Survey, News, Twitter and Search Engine Data," Papers 1112.1051, arXiv.org.
    5. Simon Alfano & Stefan Feuerriegel & Dirk Neumann, 2020. "Language sentiment in fundamental and noise trading: evidence from crude oil," Applied Economics, Taylor & Francis Journals, vol. 52(49), pages 5343-5363, October.
    6. Anil K Kashyap & Jeremy C. Stein, 2023. "Monetary Policy When the Central Bank Shapes Financial-Market Sentiment," Journal of Economic Perspectives, American Economic Association, vol. 37(1), pages 53-76, Winter.
    7. De Long, J Bradford & Andrei Shleifer & Lawrence H. Summers & Robert J. Waldmann, 1990. "Noise Trader Risk in Financial Markets," Journal of Political Economy, University of Chicago Press, vol. 98(4), pages 703-738, August.
    8. 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.
    9. Amir Fekrazad & Syed M. Harun & Naafey Sardar, 2022. "Social media sentiment and the stock market," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 46(2), pages 397-419, April.
    10. Taylan Kabbani & Fatih Enes Usta, 2022. "Predicting The Stock Trend Using News Sentiment Analysis and Technical Indicators in Spark," Papers 2201.12283, arXiv.org.
    11. Lee A. Smales, 2016. "Time-varying relationship of news sentiment, implied volatility and stock returns," Applied Economics, Taylor & Francis Journals, vol. 48(51), pages 4942-4960, November.
    12. Ser-Huang Poon & Clive W.J. Granger, 2003. "Forecasting Volatility in Financial Markets: A Review," Journal of Economic Literature, American Economic Association, vol. 41(2), pages 478-539, June.
    13. Shi, Yanlin & Ho, Kin-Yip, 2021. "News sentiment and states of stock return volatility: Evidence from long memory and discrete choice models," Finance Research Letters, Elsevier, vol. 38(C).
    14. 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.
    15. Sheung Yin Kevin Mo & Anqi Liu & Steve Y. Yang, 2016. "News sentiment to market impact and its feedback effect," Environment Systems and Decisions, Springer, vol. 36(2), pages 158-166, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Karolina Krystyniak & Hongqi Liu & Huajing Hu, 2025. "What’s Trending? Stock-Level Investor Sentiment and Returns," IJFS, MDPI, vol. 13(3), pages 1-27, August.

    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. Sobti, Neharika, 2025. "What triggers intraday price jumps and co-jumps in gold?," International Review of Financial Analysis, Elsevier, vol. 105(C).
    2. 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).
    3. Prajwal Eachempati & Praveen Ranjan Srivastava, 2021. "Accounting for unadjusted news sentiment for asset pricing," Qualitative Research in Financial Markets, Emerald Group Publishing Limited, vol. 13(3), pages 383-422, May.
    4. Hadhri, Sinda & Younus, Mehak & Naeem, Muhammad Abubakr & Yarovaya, Larisa, 2025. "Listening to the Market: Music sentiment and cryptocurrency returns," Journal of International Money and Finance, Elsevier, vol. 157(C).
    5. Wang, Wenzhao & Duxbury, Darren, 2021. "Institutional investor sentiment and the mean-variance relationship: Global evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 191(C), pages 415-441.
    6. Utku Uygur & Oktay Taş, 2014. "The impacts of investor sentiment on returns and conditional volatility of international stock markets," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(3), pages 1165-1179, May.
    7. Lin Ren & Yingyue Sun & Deping Xiong & Yu Wei, 2025. "Evaluating the Impact of Private and Public Sentiments on the Linkage Between Gold and Stock Markets: Evidence from China," Evaluation Review, , vol. 49(4), pages 739-772, August.
    8. Eric. W. K. See-To & Yang Yang, 2017. "Market sentiment dispersion and its effects on stock return and volatility," Electronic Markets, Springer;IIM University of St. Gallen, vol. 27(3), pages 283-296, August.
    9. Di, Li & Shaiban, Mohammed Sharaf & Hasanov, Akram Shavkatovich, 2021. "The power of investor sentiment in explaining bank stock performance: Listed conventional vs. Islamic banks," Pacific-Basin Finance Journal, Elsevier, vol. 66(C).
    10. Leif Brandes & Katja Rost, 2009. "Media, Limited Attention and the Propensity of Individuals to Buy Stocks," Working Papers 0098, University of Zurich, Institute for Strategy and Business Economics (ISU), revised Sep 2009.
    11. Li, Xiao & Shen, Dehua & Xue, Mei & Zhang, Wei, 2017. "Daily happiness and stock returns: The case of Chinese company listed in the United States," Economic Modelling, Elsevier, vol. 64(C), pages 496-501.
    12. Truong, Quang-Thai & Tran, Quynh-Nhu & Bakry, Walid & Nguyen, Duc Nguyen & Al-Mohamad, Somar, 2021. "Football sentiment and stock market returns: Evidence from a frontier market," Journal of Behavioral and Experimental Finance, Elsevier, vol. 30(C).
    13. Cui, Xudong & Gong, Pu & Liu, Tong, 2025. "The disposition effect and market volatility prediction," International Review of Financial Analysis, Elsevier, vol. 108(PB).
    14. Al-Nasseri, Alya & Menla Ali, Faek, 2018. "What does investors' online divergence of opinion tell us about stock returns and trading volume?," Journal of Business Research, Elsevier, vol. 86(C), pages 166-178.
    15. Yun Liu & Dengshi Huang & Jianan Zhou & Sirui Wang, 2024. "Does image sentiment of major public emergency affect the stock market performance? New insight from deep learning techniques," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 64(4), pages 4447-4472, December.
    16. 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.
    17. Ni Yang & Adrian Fernandez‐Perez & Ivan Indriawan, 2025. "The price impact of tweets: A high‐frequency study," The Financial Review, Eastern Finance Association, vol. 60(1), pages 147-171, February.
    18. Dahmene, Meriam & Boughrara, Adel & Slim, Skander, 2021. "Nonlinearity in stock returns: Do risk aversion, investor sentiment and, monetary policy shocks matter?," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 676-699.
    19. Sirio Aramonte, 2015. "Innovation, investor sentiment, and firm-level experimentation," Finance and Economics Discussion Series 2015-67, Board of Governors of the Federal Reserve System (U.S.).
    20. Heng (Emily) Wang & Xiaoyang Zhu, 2024. "Can institutional investors influence media sentiment?," International Journal of Managerial Finance, Emerald Group Publishing Limited, vol. 20(5), pages 1295-1319, April.

    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:gam:jjrfmx:v:16:y:2023:i:8:p:376-:d:1218076. 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: MDPI Indexing Manager The email address of this maintainer does not seem to be valid anymore. Please ask MDPI Indexing Manager to update the entry or send us the correct address (email available below). General contact details of provider: https://www.mdpi.com .

    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.