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

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  • 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.

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  • 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
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    as
    1. Karl B. Diether & Kuan-Hui Lee & Ingrid M. Werner, 2009. "Short-Sale Strategies and Return Predictability," 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," 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. Timothy C. Johnson, 2004. "Forecast Dispersion and the Cross Section of Expected Returns," Journal of Finance, American Finance Association, vol. 59(5), pages 1957-1978, October.
    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," 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," 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. 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.
    45. Snehal Banerjee, 2011. "Learning from Prices and the Dispersion in Beliefs," 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.
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    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

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