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Structural breaks in online investor sentiment: A note on the nonstationarity of financial chatter

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  • Ballinari, Daniele
  • Behrendt, Simon

Abstract

Given the increasing interest in investor sentiment derived from social media platforms, we address one overlooked question – are there structural breaks in online investor sentiment? We cast the problem of break-point estimation in the dynamics of the sentiment series as a model selection problem. Considering 360 stocks, we detect structural breaks in most of the respective online investor sentiment series. A return prediction exercise illustrates the economic significance of the detected structural breaks. Our results call into question the widespread practice of using online investor sentiment series without taking into account the nonstationarity induced by structural breaks.

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  • Ballinari, Daniele & Behrendt, Simon, 2020. "Structural breaks in online investor sentiment: A note on the nonstationarity of financial chatter," Finance Research Letters, Elsevier, vol. 35(C).
    • Handle: RePEc:eee:finlet:v:35:y:2020:i:c:s1544612319311821
    DOI: 10.1016/j.frl.2020.101479
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    1. Pesaran, M. Hashem & Timmermann, Allan, 2005. "Small sample properties of forecasts from autoregressive models under structural breaks," Journal of Econometrics, Elsevier, vol. 129(1-2), pages 183-217.
    2. Sanjiv R. Das & Mike Y. Chen, 2007. "Yahoo! for Amazon: Sentiment Extraction from Small Talk on the Web," Management Science, INFORMS, vol. 53(9), pages 1375-1388, September.
    3. Malcolm Baker & Jeffrey Wurgler, 2006. "Investor Sentiment and the Cross‐Section of Stock Returns," Journal of Finance, American Finance Association, vol. 61(4), pages 1645-1680, August.
    4. Audrino, Francesco & Sigrist, Fabio & Ballinari, Daniele, 2020. "The impact of sentiment and attention measures on stock market volatility," International Journal of Forecasting, Elsevier, vol. 36(2), pages 334-357.
    5. Newey, Whitney K & West, Kenneth D, 1987. "Hypothesis Testing with Efficient Method of Moments Estimation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 28(3), pages 777-787, October.
    6. 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.
    7. 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.
    8. Carhart, Mark M, 1997. "On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
    9. Davis, Richard A. & Lee, Thomas C.M. & Rodriguez-Yam, Gabriel A., 2006. "Structural Break Estimation for Nonstationary Time Series Models," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 223-239, March.
    10. Diego García, 2013. "Sentiment during Recessions," Journal of Finance, American Finance Association, vol. 68(3), pages 1267-1300, June.
    11. Michela Nardo & Marco Petracco-Giudici & Minás Naltsidis, 2016. "Walking Down Wall Street With A Tablet: A Survey Of Stock Market Predictions Using The Web," Journal of Economic Surveys, Wiley Blackwell, vol. 30(2), pages 356-369, April.
    12. Behrendt, Simon & Schmidt, Alexander, 2018. "The Twitter myth revisited: Intraday investor sentiment, Twitter activity and individual-level stock return volatility," Journal of Banking & Finance, Elsevier, vol. 96(C), pages 355-367.
    13. Boot, Tom & Pick, Andreas, 2020. "Does modeling a structural break improve forecast accuracy?," Journal of Econometrics, Elsevier, vol. 215(1), pages 35-59.
    14. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    15. Kurov, Alexander, 2010. "Investor sentiment and the stock market's reaction to monetary policy," Journal of Banking & Finance, Elsevier, vol. 34(1), pages 139-149, January.
    16. 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.
    17. Ngai Hang Chan & Chun Yip Yau & Rong-Mao Zhang, 2014. "Group LASSO for Structural Break Time Series," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(506), pages 590-599, June.
    18. Tim Loughran & Bill Mcdonald, 2011. "When Is a Liability Not a Liability? Textual Analysis, Dictionaries, and 10‐Ks," Journal of Finance, American Finance Association, vol. 66(1), pages 35-65, February.
    19. Audrino, Francesco & Tetereva, Anastasija, 2019. "Sentiment spillover effects for US and European companies," Journal of Banking & Finance, Elsevier, vol. 106(C), pages 542-567.
    20. Ming Yuan & Yi Lin, 2006. "Model selection and estimation in regression with grouped variables," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 68(1), pages 49-67, February.
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    Cited by:

    1. Bianca Raluca Baditoiu & Roxana Ioan & Valentin Partenie Munteanu & Alexandru Buglea, 2023. "Investors’ reactions on the publication of integrated reports. Evidence from European stock markets," E&M Economics and Management, Technical University of Liberec, Faculty of Economics, vol. 26(2), pages 158-171, June.
    2. Daniele Ballinari & Simon Behrendt, 2021. "How to gauge investor behavior? A comparison of online investor sentiment measures," Digital Finance, Springer, vol. 3(2), pages 169-204, June.

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    More about this item

    Keywords

    Investor sentiment; Structural breaks; Nonstationarity; Group Lasso;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • G40 - Financial Economics - - Behavioral Finance - - - General

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