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News sentiment to market impact and its feedback effect

Author

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  • Sheung Yin Kevin Mo

    (Stevens Institute of Technology)

  • Anqi Liu

    (Stevens Institute of Technology)

  • Steve Y. Yang

    (Stevens Institute of Technology)

Abstract

Although market feedback on investor sentiment effect has been conceptually identified in the existing finance literature and investment strategies have been designed to explore this effect, there lacks systematic analysis in a quantified manner on such effect. Digitization of news articles and the advancement of computational intelligence applications have led to a growing influence of news sentiment over financial markets in recent years. News sentiment has often been used as a proxy for gauging investor sentiment and reflecting the aggregate confidence of the society toward future market. Previous studies have primarily focused on elucidating the unidirectional impact of news sentiment on market returns and not vice versa. In this study, we analyze more than 12 millions of news articles and document the presence of a significant feedback effect between news sentiment and market returns across the major indices in the US financial market. More specifically, we find that news sentiment exhibits a lag-5 effect on market returns and conversely market returns elicit consistent lag-1 effects on news sentiment. This aligns well with our intuition that news sentiment drives trading activity and investment decisions. In turn, heightened investment activity further stimulates involuntary responses, which manifest in the form of more news coverage and publications. The evidence presented highlights the strong correlation between news sentiment and market returns and demonstrates the benefits of advancing knowledge in data-driven modeling and its interaction with market movements.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:envsyd:v:36:y:2016:i:2:d:10.1007_s10669-016-9590-9
    DOI: 10.1007/s10669-016-9590-9
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    References listed on IDEAS

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    Cited by:

    1. Jitendra Kumar Rout & Kim-Kwang Raymond Choo & Amiya Kumar Dash & Sambit Bakshi & Sanjay Kumar Jena & Karen L. Williams, 2018. "A model for sentiment and emotion analysis of unstructured social media text," Electronic Commerce Research, Springer, vol. 18(1), pages 181-199, March.
    2. Aneeta Elsa Simon & Manu K.S., 2023. "Does Sentiments Impact the Returns of Commodity Derivatives? An Evidence from Multi-commodity Exchange India," Vision, , vol. 27(1), pages 79-92, February.
    3. Qifeng Qiao & Peter A. Beling, 2016. "Decision analytics and machine learning in economic and financial systems," Environment Systems and Decisions, Springer, vol. 36(2), pages 109-113, June.

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