IDEAS home Printed from https://ideas.repec.org/a/inm/ormksc/v31y2012i2p198-215.html
   My bibliography  Save this article

Does Chatter Really Matter? Dynamics of User-Generated Content and Stock Performance

Author

Listed:
  • Seshadri Tirunillai

    (C.T. Bauer College of Business, University of Houston, Houston, Texas 77204)

  • Gerard J. Tellis

    (Marshall School of Business, University of Southern California, Los Angeles, California 90089)

Abstract

This study examines whether user-generated content (UGC) is related to stock market performance, which metric of UGC has the strongest relationship, and what the dynamics of the relationship are. We aggregate UGC from multiple websites over a four-year period across 6 markets and 15 firms. We derive multiple metrics of UGC and use multivariate time-series models to assess the relationship between UGC and stock market performance. Volume of chatter significantly leads abnormal returns by a few days (supported by Granger causality tests). Of all the metrics of UGC, volume of chatter has the strongest positive effect on abnormal returns and trading volume. The effect of negative and positive metrics of UGC on abnormal returns is asymmetric. Whereas negative UGC has a significant negative effect on abnormal returns with a short "wear-in" and long "wear-out," positive UGC has no significant effect on these metrics. The volume of chatter and negative chatter have a significant positive effect on trading volume. Idiosyncratic risk increases significantly with negative information in UGC. Positive information does not have much influence on the risk of the firm. An increase in off-line advertising significantly increases the volume of chatter and decreases negative chatter. These results have important implications for managers and investors.

Suggested Citation

  • Seshadri Tirunillai & Gerard J. Tellis, 2012. "Does Chatter Really Matter? Dynamics of User-Generated Content and Stock Performance," Marketing Science, INFORMS, vol. 31(2), pages 198-215, March.
  • Handle: RePEc:inm:ormksc:v:31:y:2012:i:2:p:198-215
    DOI: 10.1287/mksc.1110.0682
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mksc.1110.0682
    Download Restriction: no

    File URL: https://libkey.io/10.1287/mksc.1110.0682?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
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. John Y. Campbell & Sanford J. Grossman & Jiang Wang, 1993. "Trading Volume and Serial Correlation in Stock Returns," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 108(4), pages 905-939.
    3. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    4. Harrison Hong & Jeremy C. Stein, 1999. "A Unified Theory of Underreaction, Momentum Trading, and Overreaction in Asset Markets," Journal of Finance, American Finance Association, vol. 54(6), pages 2143-2184, December.
    5. Wei Huang & Qianqiu Liu & S. Ghon Rhee & Liang Zhang, 2010. "Return Reversals, Idiosyncratic Risk, and Expected Returns," The Review of Financial Studies, Society for Financial Studies, vol. 23(1), pages 147-168, January.
    6. Andrew W. Lo, A. Craig MacKinlay, 1988. "Stock Market Prices do not Follow Random Walks: Evidence from a Simple Specification Test," The Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 41-66.
    7. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    8. Dhar, Vasant & Chang, Elaine A., 2009. "Does Chatter Matter? The Impact of User-Generated Content on Music Sales," Journal of Interactive Marketing, Elsevier, vol. 23(4), pages 300-307.
    9. 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.
    10. Tarun Chordia & Bhaskaran Swaminathan, 2000. "Trading Volume and Cross‐Autocorrelations in Stock Returns," Journal of Finance, American Finance Association, vol. 55(2), pages 913-935, April.
    11. Jaffe, Jeffrey F, 1974. "Special Information and Insider Trading," The Journal of Business, University of Chicago Press, vol. 47(3), pages 410-428, July.
    12. Pesaran, H. Hashem & Shin, Yongcheol, 1998. "Generalized impulse response analysis in linear multivariate models," Economics Letters, Elsevier, vol. 58(1), pages 17-29, January.
    13. 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.
    14. Pesaran, M. Hashem & Smith, Ron, 1995. "Estimating long-run relationships from dynamic heterogeneous panels," Journal of Econometrics, Elsevier, vol. 68(1), pages 79-113, July.
    15. Holtz-Eakin, Douglas & Newey, Whitney & Rosen, Harvey S, 1988. "Estimating Vector Autoregressions with Panel Data," Econometrica, Econometric Society, vol. 56(6), pages 1371-1395, November.
    16. Gerard J. Tellis & Philip Hans Franses, 2006. "Optimal Data Interval for Estimating Advertising Response," Marketing Science, INFORMS, vol. 25(3), pages 217-229, 05-06.
    17. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    18. 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.
    19. David Godes & Dina Mayzlin, 2004. "Using Online Conversations to Study Word-of-Mouth Communication," Marketing Science, INFORMS, vol. 23(4), pages 545-560, June.
    20. Gerard J. Tellis & Joseph Johnson, 2007. "The Value of Quality," Marketing Science, INFORMS, vol. 26(6), pages 758-773, 11-12.
    21. Mitchell, Mark L & Mulherin, J Harold, 1994. "The Impact of Public Information on the Stock Market," Journal of Finance, American Finance Association, vol. 49(3), pages 923-950, July.
    22. Carhart, Mark M, 1997. "On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
    23. Engle, Robert F & Ng, Victor K, 1993. "Measuring and Testing the Impact of News on Volatility," Journal of Finance, American Finance Association, vol. 48(5), pages 1749-1778, December.
    24. Avramov, Doron & Chordia, Tarun & Jostova, Gergana & Philipov, Alexander, 2009. "Credit ratings and the cross-section of stock returns," Journal of Financial Markets, Elsevier, vol. 12(3), pages 469-499, August.
    25. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
    26. Yubo Chen & Jinhong Xie, 2008. "Online Consumer Review: Word-of-Mouth as a New Element of Marketing Communication Mix," Management Science, INFORMS, vol. 54(3), pages 477-491, March.
    27. Mandelker, Gershon, 1974. "Risk and return: The case of merging firms," Journal of Financial Economics, Elsevier, vol. 1(4), pages 303-335, December.
    28. Michael A. Wiles & Shailendra P. Jain & Saurabh Mishra & Charles Lindsey, 2010. "Stock Market Response to Regulatory Reports of Deceptive Advertising: The Moderating Effect of Omission Bias and Firm Reputation," Marketing Science, INFORMS, vol. 29(5), pages 828-845, 09-10.
    29. Koen Pauwels & Shuba Srinivasan, 2004. "Who Benefits from Store Brand Entry?," Marketing Science, INFORMS, vol. 23(3), pages 364-390, July.
    30. Chris Forman & Anindya Ghose & Batia Wiesenfeld, 2008. "Examining the Relationship Between Reviews and Sales: The Role of Reviewer Identity Disclosure in Electronic Markets," Information Systems Research, INFORMS, vol. 19(3), pages 291-313, September.
    31. Fu, Fangjian, 2009. "Idiosyncratic risk and the cross-section of expected stock returns," Journal of Financial Economics, Elsevier, vol. 91(1), pages 24-37, January.
    32. Xueming Luo, 2009. "Quantifying the Long-Term Impact of Negative Word of Mouth on Cash Flows and Stock Prices," Marketing Science, INFORMS, vol. 28(1), pages 148-165, 01-02.
    33. Marc Vanhuele & Shuba Srinivasan & Koen Pauwels, 2010. "Mindset Metrics in Market Response Models: An Integrative Approach," Post-Print hal-00528411, HAL.
    34. Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501.
    35. Healy, Paul M. & Palepu, Krishna G., 2001. "Information asymmetry, corporate disclosure, and the capital markets: A review of the empirical disclosure literature," Journal of Accounting and Economics, Elsevier, vol. 31(1-3), pages 405-440, September.
    36. Pradeep K. Chintagunta & Shyam Gopinath & Sriram Venkataraman, 2010. "The Effects of Online User Reviews on Movie Box Office Performance: Accounting for Sequential Rollout and Aggregation Across Local Markets," Marketing Science, INFORMS, vol. 29(5), pages 944-957, 09-10.
    37. Ashish Sood & Gerard J. Tellis, 2009. "Do Innovations Really Pay Off? Total Stock Market Returns to Innovation," Marketing Science, INFORMS, vol. 28(3), pages 442-456, 05-06.
    38. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September.
    Full references (including those not matched with items on IDEAS)

    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. Tirunillai, S. & Tellis, G.J., 2011. "Does Online Chatter Really Matter? Dynamics of User-Generated Content and Stock Performance," ERIM Report Series Research in Management 25817, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    2. Xueming Luo & Jie Zhang & Wenjing Duan, 2013. "Social Media and Firm Equity Value," Information Systems Research, INFORMS, vol. 24(1), pages 146-163, March.
    3. Keunbae Ahn, 2021. "Predictable Fluctuations in the Cross-Section and Time-Series of Asset Prices," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 1-2021.
    4. Ahmad, Khurshid & Han, JingGuang & Hutson, Elaine & Kearney, Colm & Liu, Sha, 2016. "Media-expressed negative tone and firm-level stock returns," Journal of Corporate Finance, Elsevier, vol. 37(C), pages 152-172.
    5. 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.
    6. Amit Goyal, 2012. "Empirical cross-sectional asset pricing: a survey," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 26(1), pages 3-38, March.
    7. Patrick Houlihan & Germán G. Creamer, 2021. "Leveraging Social Media to Predict Continuation and Reversal in Asset Prices," Computational Economics, Springer;Society for Computational Economics, vol. 57(2), pages 433-453, February.
    8. Kearney, Colm & Liu, Sha, 2014. "Textual sentiment in finance: A survey of methods and models," International Review of Financial Analysis, Elsevier, vol. 33(C), pages 171-185.
    9. Wang, Zijun, 2021. "The high volume return premium and economic fundamentals," Journal of Financial Economics, Elsevier, vol. 140(1), pages 325-345.
    10. Brockman, Paul & Guo, Tao & Vivero, Maria Gabriela & Yu, Wayne, 2022. "Is idiosyncratic risk priced? The international evidence," Journal of Empirical Finance, Elsevier, vol. 66(C), pages 121-136.
    11. Kick, Markus, 2015. "Social Media Research: A Narrative Review," EconStor Preprints 182506, ZBW - Leibniz Information Centre for Economics.
    12. Gu, Chen & Kurov, Alexander, 2020. "Informational role of social media: Evidence from Twitter sentiment," Journal of Banking & Finance, Elsevier, vol. 121(C).
    13. Khim-Yong Goh & Cheng-Suang Heng & Zhijie Lin, 2013. "Social Media Brand Community and Consumer Behavior: Quantifying the Relative Impact of User- and Marketer-Generated Content," Information Systems Research, INFORMS, vol. 24(1), pages 88-107, March.
    14. Xiaofei Zhao, 2017. "Does Information Intensity Matter for Stock Returns? Evidence from Form 8-K Filings," Management Science, INFORMS, vol. 63(5), pages 1382-1404, May.
    15. Geweke, J. & Joel Horowitz & Pesaran, M.H., 2006. "Econometrics: A Bird’s Eye View," Cambridge Working Papers in Economics 0655, Faculty of Economics, University of Cambridge.
    16. Wang, Yuming & Ma, Jinpeng, 2014. "Excess volatility and the cross-section of stock returns," The North American Journal of Economics and Finance, Elsevier, vol. 27(C), pages 1-16.
    17. Cao, Jie & Han, Bing, 2016. "Idiosyncratic risk, costly arbitrage, and the cross-section of stock returns," Journal of Banking & Finance, Elsevier, vol. 73(C), pages 1-15.
    18. Sood, Ashish & Kappe, Eelco & Stremersch, Stefan, 2014. "The commercial contribution of clinical studies for pharmaceutical drugs," International Journal of Research in Marketing, Elsevier, vol. 31(1), pages 65-77.
    19. Jennie Bai & Turan G. Bali & Quan Wen, 2019. "Is There a Risk-Return Tradeoff in the Corporate Bond Market? Time-Series and Cross-Sectional Evidence," NBER Working Papers 25995, National Bureau of Economic Research, Inc.
    20. Jim Kyung-Soo Liew & Zhechao Zhou, 2014. "Initial Investigations of Intra-Day News Flow of S&P500 Constituents," Risks, MDPI, vol. 2(2), pages 1-14, April.

    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:inm:ormksc:v:31:y:2012:i:2:p:198-215. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.