IDEAS home Printed from https://ideas.repec.org/a/eee/jbrese/v86y2018icp166-178.html
   My bibliography  Save this article

What does investors' online divergence of opinion tell us about stock returns and trading volume?

Author

Listed:
  • Al-Nasseri, Alya
  • Menla Ali, Faek

Abstract

We analyse 289,443 online tweets from StockTwits and construct a divergence of opinion (disagreement) indicator for investigating the impact of disagreement on stock returns and trading volume. We find that the impact of disagreement on returns is asymmetric; it is negative (positive) during bull (bear) market periods. We also find that higher online disagreement increases trading volume; this effect is detected irrespective of whether the market is bullish or bearish. Moreover, portfolio strategies that are designed on the basis of our disagreement indicator are shown to generate abnormal profits. Overall, our results confirm the important role of belief dispersion in financial markets.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:jbrese:v:86:y:2018:i:c:p:166-178
    DOI: 10.1016/j.jbusres.2018.01.006
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0148296318300067
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jbusres.2018.01.006?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Karl B. Diether & Kuan-Hui Lee & Ingrid M. Werner, 2009. "Short-Sale Strategies and Return Predictability," The Review of Financial Studies, Society for Financial Studies, vol. 22(2), pages 575-607, February.
    2. Karl B. Diether & Christopher J. Malloy & Anna Scherbina, 2002. "Differences of Opinion and the Cross Section of Stock Returns," Journal of Finance, American Finance Association, vol. 57(5), pages 2113-2141, October.
    3. Yuan, Yu, 2015. "Market-wide attention, trading, and stock returns," Journal of Financial Economics, Elsevier, vol. 116(3), pages 548-564.
    4. Tarun Chordia & Richard Roll & Avanidhar Subrahmanyam, 2001. "Market Liquidity and Trading Activity," Journal of Finance, American Finance Association, vol. 56(2), pages 501-530, April.
    5. Harrison Hong & Jeremy C. Stein, 2003. "Differences of Opinion, Short-Sales Constraints, and Market Crashes," The Review of Financial Studies, Society for Financial Studies, vol. 16(2), pages 487-525.
    6. D’Amuri, Francesco & Marcucci, Juri, 2017. "The predictive power of Google searches in forecasting US unemployment," International Journal of Forecasting, Elsevier, vol. 33(4), pages 801-816.
    7. Huina Mao & Scott Counts & Johan Bollen, 2011. "Predicting Financial Markets: Comparing Survey, News, Twitter and Search Engine Data," Papers 1112.1051, arXiv.org.
    8. Kandel, Eugene & Pearson, Neil D, 1995. "Differential Interpretation of Public Signals and Trade in Speculative Markets," Journal of Political Economy, University of Chicago Press, vol. 103(4), pages 831-872, August.
    9. Baker, Malcolm & Stein, Jeremy C., 2004. "Market liquidity as a sentiment indicator," Journal of Financial Markets, Elsevier, vol. 7(3), pages 271-299, June.
    10. Chen, Joseph & Hong, Harrison & Stein, Jeremy C., 2002. "Breadth of ownership and stock returns," Journal of Financial Economics, Elsevier, vol. 66(2-3), pages 171-205.
    11. Milgrom, Paul & Stokey, Nancy, 1982. "Information, trade and common knowledge," Journal of Economic Theory, Elsevier, vol. 26(1), pages 17-27, February.
    12. Zhang, Wei & Li, Xiao & Shen, Dehua & Teglio, Andrea, 2016. "Daily happiness and stock returns: Some international evidence," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 460(C), pages 201-209.
    13. 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.
    14. Branislav Saxa, 2014. "Forecasting Mortgages: Internet Search Data as a Proxy for Mortgage Credit Demand," Working Papers 2014/14, Czech National Bank.
    15. Yu, Jialin, 2011. "Disagreement and return predictability of stock portfolios," Journal of Financial Economics, Elsevier, vol. 99(1), pages 162-183, January.
    16. Alexander David, 2008. "Heterogeneous Beliefs, Speculation, and the Equity Premium," Journal of Finance, American Finance Association, vol. 63(1), pages 41-83, February.
    17. Lakonishok, Josef & Maberly, Edwin, 1990. "The Weekend Effect: Trading Patterns of Individual and Institutional Investors," Journal of Finance, American Finance Association, vol. 45(1), pages 231-243, March.
    18. Paul C. Tetlock & Maytal Saar‐Tsechansky & Sofus Macskassy, 2008. "More Than Words: Quantifying Language to Measure Firms' Fundamentals," Journal of Finance, American Finance Association, vol. 63(3), pages 1437-1467, June.
    19. Verma, Rahul & Verma, Priti, 2007. "Noise trading and stock market volatility," Journal of Multinational Financial Management, Elsevier, vol. 17(3), pages 231-243, July.
    20. Lee, Wayne Y. & Jiang, Christine X. & Indro, Daniel C., 2002. "Stock market volatility, excess returns, and the role of investor sentiment," Journal of Banking & Finance, Elsevier, vol. 26(12), pages 2277-2299.
    21. Amihud, Yakov, 2002. "Illiquidity and stock returns: cross-section and time-series effects," Journal of Financial Markets, Elsevier, vol. 5(1), pages 31-56, January.
    22. McLaren, Nick & Shanbhogue, Rachana, 2011. "Using internet search data as economic indicators," Bank of England Quarterly Bulletin, Bank of England, vol. 51(2), pages 134-140.
    23. Thaler, Richard H, 1987. "Seasonal Movements in Security Prices II: Weekend, Holiday, Turn of the Month, and Intraday Effects," Journal of Economic Perspectives, American Economic Association, vol. 1(2), pages 169-177, Fall.
    24. Lily Fang & Joel Peress, 2009. "Media Coverage and the Cross‐section of Stock Returns," Journal of Finance, American Finance Association, vol. 64(5), pages 2023-2052, October.
    25. repec:bla:jfinan:v:59:y:2004:i:5:p:1957-1978 is not listed on IDEAS
    26. Narasimhan Jegadeesh & Sheridan Titman, 2001. "Profitability of Momentum Strategies: An Evaluation of Alternative Explanations," Journal of Finance, American Finance Association, vol. 56(2), pages 699-720, April.
    27. Ronnie Sadka & Anna Scherbina, 2007. "Analyst Disagreement, Mispricing, and Liquidity," Journal of Finance, American Finance Association, vol. 62(5), pages 2367-2403, October.
    28. Chen, Lin & Qin, Lu & Zhu, Hongquan, 2015. "Opinion divergence, unexpected trading volume and stock returns: Evidence from China," International Review of Economics & Finance, Elsevier, vol. 36(C), pages 119-127.
    29. Bukovina, Jaroslav, 2016. "Social media big data and capital markets—An overview," Journal of Behavioral and Experimental Finance, Elsevier, vol. 11(C), pages 18-26.
    30. Josef Lakonishok, Seymour Smidt, 1988. "Are Seasonal Anomalies Real? A Ninety-Year Perspective," The Review of Financial Studies, Society for Financial Studies, vol. 1(4), pages 403-425.
    31. Berkman, Henk & Dimitrov, Valentin & Jain, Prem C. & Koch, Paul D. & Tice, Sheri, 2009. "Sell on the news: Differences of opinion, short-sales constraints, and returns around earnings announcements," Journal of Financial Economics, Elsevier, vol. 92(3), pages 376-399, June.
    32. Carlin, Bruce I. & Longstaff, Francis A. & Matoba, Kyle, 2014. "Disagreement and asset prices," Journal of Financial Economics, Elsevier, vol. 114(2), pages 226-238.
    33. Snehal Banerjee & Ilan Kremer, 2010. "Disagreement and Learning: Dynamic Patterns of Trade," Journal of Finance, American Finance Association, vol. 65(4), pages 1269-1302, August.
    34. Hyunyoung Choi & Hal Varian, 2012. "Predicting the Present with Google Trends," The Economic Record, The Economic Society of Australia, vol. 88(s1), pages 2-9, June.
    35. Jon A. Garfinkel & Jonathan Sokobin, 2006. "Volume, Opinion Divergence, and Returns: A Study of Post–Earnings Announcement Drift," Journal of Accounting Research, Wiley Blackwell, vol. 44(1), pages 85-112, March.
    36. Doukas, John A. & Kim, Chansog & Pantzalis, Christos, 2006. "Divergence of opinion and equity returns under different states of earnings expectations," Journal of Financial Markets, Elsevier, vol. 9(3), pages 310-331, August.
    37. Charles M.C. Lee & Bhaskaran Swaminathan, 2000. "Price Momentum and Trading Volume," Journal of Finance, American Finance Association, vol. 55(5), pages 2017-2069, October.
    38. 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.
    39. Miller, Edward M, 1977. "Risk, Uncertainty, and Divergence of Opinion," Journal of Finance, American Finance Association, vol. 32(4), pages 1151-1168, September.
    40. Verardo, Michela, 2009. "Heterogeneous Beliefs and Momentum Profits," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 44(4), pages 795-822, August.
    41. Varian, Hal R, 1985. "Divergence of Opinion in Complete Markets: A Note," Journal of Finance, American Finance Association, vol. 40(1), pages 309-317, March.
    42. Harris, Milton & Raviv, Artur, 1993. "Differences of Opinion Make a Horse Race," The Review of Financial Studies, Society for Financial Studies, vol. 6(3), pages 473-506.
    43. 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.
    44. repec:bla:jfinan:v:59:y:2004:i:3:p:1259-1294 is not listed on IDEAS
    45. Snehal Banerjee, 2011. "Learning from Prices and the Dispersion in Beliefs," The Review of Financial Studies, Society for Financial Studies, vol. 24(9), pages 3025-3068.
    46. Chung, San-Lin & Hung, Chi-Hsiou & Yeh, Chung-Ying, 2012. "When does investor sentiment predict stock returns?," Journal of Empirical Finance, Elsevier, vol. 19(2), pages 217-240.
    47. Doukas, John A. & Kim, Chansog (Francis) & Pantzalis, Christos, 2006. "Divergence of Opinion and Equity Returns," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 41(3), pages 573-606, September.
    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. Teplova, T. & Sokolova, T. & Tomtosov, A. & Buchko, D. & Nikulin, D., 2022. "The sentiment of private investors in explaining the differences in the trade characteristics of the Russian market stocks," Journal of the New Economic Association, New Economic Association, vol. 53(1), pages 53-84.
    2. Huang, Jianbai & Tang, Jing & Zhang, Hongwei, 2020. "The effect of investors’ information search behaviors on rebar market return dynamics using high frequency data," Resources Policy, Elsevier, vol. 66(C).
    3. Jing Zhou & Silin Ye & Wei Lan & Yunwen Jiang, 2021. "The effect of social media on corporate violations: Evidence from Weibo posts in China," International Review of Finance, International Review of Finance Ltd., vol. 21(3), pages 966-988, September.
    4. Wang, Gang-Jin & Xiong, Lu & Zhu, You & Xie, Chi & Foglia, Matteo, 2022. "Multilayer network analysis of investor sentiment and stock returns," Research in International Business and Finance, Elsevier, vol. 62(C).
    5. Jeremy K. Nguyen & Adam Karg & Abbas Valadkhani & Heath McDonald, 2022. "Predicting individual event attendance with machine learning: a ‘step-forward’ approach," Applied Economics, Taylor & Francis Journals, vol. 54(27), pages 3138-3153, June.
    6. Dominik M. Piehlmaier, 2022. "Overconfidence and the adoption of robo-advice: why overconfident investors drive the expansion of automated financial advice," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-24, December.
    7. Caporale, Guglielmo Maria & Menla Ali, Faek & Spagnolo, Fabio & Spagnolo, Nicola, 2022. "Cross-border portfolio flows and news media coverage," Journal of International Money and Finance, Elsevier, vol. 126(C).
    8. Zhang, Zuochao & Goodell, John W. & Shen, Dehua & Lahmar, Oumaima, 2024. "Media opinion divergence and stock returns: Evidence from China," International Review of Financial Analysis, Elsevier, vol. 93(C).
    9. Kim, Junwoo & Kim, Robert & Kim, Sangwan, 2020. "Does financial statement comparability mitigate delayed trading volume before earnings announcements?," Journal of Business Research, Elsevier, vol. 107(C), pages 62-75.

    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. Hillert, Alexander & Jacobs, Heiko & Müller, Sebastian, 2018. "Journalist disagreement," Journal of Financial Markets, Elsevier, vol. 41(C), pages 57-76.
    2. Al-Nasseri, Alya & Menla Ali, Faek & Tucker, Allan, 2021. "Investor sentiment and the dispersion of stock returns: Evidence based on the social network of investors," International Review of Financial Analysis, Elsevier, vol. 78(C).
    3. Adem Atmaz & Suleyman Basak, 2018. "Belief Dispersion in the Stock Market," Journal of Finance, American Finance Association, vol. 73(3), pages 1225-1279, June.
    4. Gao, George P. & Lu, Xiaomeng & Song, Zhaogang & Yan, Hongjun, 2019. "Disagreement beta," Journal of Monetary Economics, Elsevier, vol. 107(C), pages 96-113.
    5. Hirota, Shinichi, 2023. "Money supply, opinion dispersion, and stock prices," Journal of Economic Behavior & Organization, Elsevier, vol. 212(C), pages 1286-1310.
    6. Andreou, Panayiotis C. & Kagkadis, Anastasios & Philip, Dennis & Tuneshev, Ruslan, 2018. "Differences in options investors’ expectations and the cross-section of stock returns," Journal of Banking & Finance, Elsevier, vol. 94(C), pages 315-336.
    7. Wei Xiong, 2013. "Bubbles, Crises, and Heterogeneous Beliefs," NBER Working Papers 18905, National Bureau of Economic Research, Inc.
    8. Hu, Yingyi & Zhao, Tiao & Zhang, Lin, 2020. "Noise trading, institutional trading, and opinion divergence: Evidence on intraday data in the Chinese stock market," International Review of Economics & Finance, Elsevier, vol. 68(C), pages 74-89.
    9. Giannini, Robert & Irvine, Paul & Shu, Tao, 2019. "The convergence and divergence of investors' opinions around earnings news: Evidence from a social network," Journal of Financial Markets, Elsevier, vol. 42(C), pages 94-120.
    10. Chen, Lin & Qin, Lu & Zhu, Hongquan, 2015. "Opinion divergence, unexpected trading volume and stock returns: Evidence from China," International Review of Economics & Finance, Elsevier, vol. 36(C), pages 119-127.
    11. Akbas, Ferhat & Boehmer, Ekkehart & Jiang, Chao & Koch, Paul D., 2022. "Overnight returns, daytime reversals, and future stock returns," Journal of Financial Economics, Elsevier, vol. 145(3), pages 850-875.
    12. Carlin, Bruce I. & Longstaff, Francis A. & Matoba, Kyle, 2014. "Disagreement and asset prices," Journal of Financial Economics, Elsevier, vol. 114(2), pages 226-238.
    13. Bruce I. Carlin & Francis A. Longstaff & Kyle Matoba, 2012. "Disagreement and Asset Prices," NBER Working Papers 18619, National Bureau of Economic Research, Inc.
    14. Zhang, Zuochao & Goodell, John W. & Shen, Dehua & Lahmar, Oumaima, 2024. "Media opinion divergence and stock returns: Evidence from China," International Review of Financial Analysis, Elsevier, vol. 93(C).
    15. 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.
    16. Chen, Tao, 2020. "Does news affect disagreement in global markets?," Journal of Business Research, Elsevier, vol. 109(C), pages 174-183.
    17. Sheng, Xuguang (Simon) & Thevenot, Maya, 2015. "Quantifying differential interpretation of public information using financial analysts’ earnings forecasts," International Journal of Forecasting, Elsevier, vol. 31(2), pages 515-530.
    18. D’Augusta, Carlo & De Vito, Antonio & Grossetti, Francesco, 2023. "Words and numbers: A disagreement story from post-earnings announcement return and volume patterns," Finance Research Letters, Elsevier, vol. 54(C).
    19. Jeffrey Hobbs & Hei Wai Lee & Vivek Singh, 2017. "New evidence on the effect of belief heterogeneity on stock returns," Review of Quantitative Finance and Accounting, Springer, vol. 48(2), pages 289-309, February.
    20. Turan G. Bali & Andriy Bodnaruk & Anna Scherbina & Yi Tang, 2018. "Unusual News Flow and the Cross Section of Stock Returns," Management Science, INFORMS, vol. 64(9), pages 4137-4155, September.

    More about this item

    Keywords

    Disagreement; Online tweets; Stock returns; Trading volume;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • G02 - Financial Economics - - General - - - Behavioral Finance: Underlying Principles
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

    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:eee:jbrese:v:86:y:2018:i:c:p:166-178. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jbusres .

    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.