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Comovements between multidimensional investor sentiment and returns on internet financial products

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  • Chen, Rongda
  • Wang, Shengnan
  • Jin, Chenglu
  • Yu, Jingjing
  • Zhang, Xinyu
  • Zhang, Shuonan

Abstract

We establish multidimensional investor sentiments of Internet financial products (ISIFP) using a text mining method and data from WeChat subscriptions in China. Our comprehensive ISIFP measure is more affected by negative sentiment information. We investigate eight dimensions of ISIFP and find that seven sentiments (joy, anger, sadness, fear, calmness, disgust, and surprise) increase market risk and decrease expected returns, whereas the goodness sentiment has a leverage effect on returns on Internet financial products (IFPs). The dimensions of ISIFP have different impacts on returns on IFPs at different quantiles.

Suggested Citation

  • Chen, Rongda & Wang, Shengnan & Jin, Chenglu & Yu, Jingjing & Zhang, Xinyu & Zhang, Shuonan, 2023. "Comovements between multidimensional investor sentiment and returns on internet financial products," International Review of Financial Analysis, Elsevier, vol. 85(C).
    • Handle: RePEc:eee:finana:v:85:y:2023:i:c:s1057521922003830
    DOI: 10.1016/j.irfa.2022.102433
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    1. Guo, Yanhong & Zhou, Wenjun & Luo, Chunyu & Liu, Chuanren & Xiong, Hui, 2016. "Instance-based credit risk assessment for investment decisions in P2P lending," European Journal of Operational Research, Elsevier, vol. 249(2), pages 417-426.
    2. Ma, Wei & Li, Haiqi & Park, Sung Y., 2017. "Empirical conditional quantile test for purchasing power parity: Evidence from East Asian countries," International Review of Economics & Finance, Elsevier, vol. 49(C), pages 211-222.
    3. Huang, Yuqin & Qiu, Huiyan & Wu, Zhiguo, 2016. "Local bias in investor attention: Evidence from China's Internet stock message boards," Journal of Empirical Finance, Elsevier, vol. 38(PA), pages 338-354.
    4. Renault, Thomas, 2017. "Intraday online investor sentiment and return patterns in the U.S. stock market," Journal of Banking & Finance, Elsevier, vol. 84(C), pages 25-40.
    5. Malcolm Baker & Jeffrey Wurgler, 2007. "Investor Sentiment in the Stock Market," Journal of Economic Perspectives, American Economic Association, vol. 21(2), pages 129-152, Spring.
    6. 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.
    7. Thomas Renault, 2017. "Intraday online investor sentiment and return patterns in the U.S. stock market," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-03205113, HAL.
    8. Ashish Agarwal & Alvin Chung Man Leung & Prabhudev Konana & Alok Kumar, 2017. "Cosearch Attention and Stock Return Predictability in Supply Chains," Information Systems Research, INFORMS, vol. 28(2), pages 265-288, June.
    9. Shen, Junyan & Yu, Jianfeng & Zhao, Shen, 2017. "Investor sentiment and economic forces," Journal of Monetary Economics, Elsevier, vol. 86(C), pages 1-21.
    10. David Yermack, 2017. "Corporate Governance and Blockchains," Review of Finance, European Finance Association, vol. 21(1), pages 7-31.
    11. Brian M. Lucey & Michael Dowling, 2005. "The Role of Feelings in Investor Decision‐Making," Journal of Economic Surveys, Wiley Blackwell, vol. 19(2), pages 211-237, April.
    12. Kim, Soon-Ho & Kim, Dongcheol, 2014. "Investor sentiment from internet message postings and the predictability of stock returns," Journal of Economic Behavior & Organization, Elsevier, vol. 107(PB), pages 708-729.
    13. Huan Tang, 2019. "Peer-to-Peer Lenders Versus Banks: Substitutes or Complements?," The Review of Financial Studies, Society for Financial Studies, vol. 32(5), pages 1900-1938.
    14. Danbolt, Jo & Siganos, Antonios & Vagenas-Nanos, Evangelos, 2015. "Investor sentiment and bidder announcement abnormal returns," Journal of Corporate Finance, Elsevier, vol. 33(C), pages 164-179.
    15. Dashan Huang & Fuwei Jiang & Jun Tu & Guofu Zhou, 2015. "Investor Sentiment Aligned: A Powerful Predictor of Stock Returns," The Review of Financial Studies, Society for Financial Studies, vol. 28(3), pages 791-837.
    16. Gregory W. Brown & Michael T. Cliff, 2005. "Investor Sentiment and Asset Valuation," The Journal of Business, University of Chicago Press, vol. 78(2), pages 405-440, March.
    17. Siganos, Antonios & Vagenas-Nanos, Evangelos & Verwijmeren, Patrick, 2014. "Facebook's daily sentiment and international stock markets," Journal of Economic Behavior & Organization, Elsevier, vol. 107(PB), pages 730-743.
    18. Chen, Rongda & Yu, Jingjing & Jin, Chenglu & Bao, Weiwei, 2019. "Internet finance investor sentiment and return comovement," Pacific-Basin Finance Journal, Elsevier, vol. 56(C), pages 151-161.
    19. Timm O. Sprenger & Andranik Tumasjan & Philipp G. Sandner & Isabell M. Welpe, 2014. "Tweets and Trades: the Information Content of Stock Microblogs," European Financial Management, European Financial Management Association, vol. 20(5), pages 926-957, November.
    20. Werner Antweiler & Murray Z. Frank, 2004. "Is All That Talk Just Noise? The Information Content of Internet Stock Message Boards," Journal of Finance, American Finance Association, vol. 59(3), pages 1259-1294, June.
    21. Chen, Rongda & Wei, Bo & Jin, Chenglu & Liu, Jia, 2021. "Returns and volatilities of energy futures markets: Roles of speculative and hedging sentiments," International Review of Financial Analysis, Elsevier, vol. 76(C).
    22. Nofer, Michael & Hinz, Oliver, 2015. "Using Twitter to Predict the Stock Market: Where is the Mood Effect?," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 77140, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    23. Rongda Chen & Huiwen Chen & Chenglu Jin & Bo Wei & Lean Yu, 2020. "Linkages and Spillovers between Internet Finance and Traditional Finance: Evidence from China," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 56(6), pages 1196-1210, May.
    24. Ali Siddiq Alhakami & Paul Slovic, 1994. "A Psychological Study of the Inverse Relationship Between Perceived Risk and Perceived Benefit," Risk Analysis, John Wiley & Sons, vol. 14(6), pages 1085-1096, December.
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