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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
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    References listed on IDEAS

    as
    1. 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.
    2. Huina Mao & Scott Counts & Johan Bollen, 2011. "Predicting Financial Markets: Comparing Survey, News, Twitter and Search Engine Data," Papers 1112.1051, arXiv.org.
    3. 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.
    4. 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.
    5. Taylan Kabbani & Fatih Enes Usta, 2022. "Predicting The Stock Trend Using News Sentiment Analysis and Technical Indicators in Spark," Papers 2201.12283, arXiv.org.
    6. 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).
    7. Mr. Sunil Sharma & Sushil Bikhchandani, 2000. "Herd Behavior in Financial Markets: A Review," IMF Working Papers 2000/048, International Monetary Fund.
    8. 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.
    9. 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.
    10. 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.
    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. 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.
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