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Industry-level media tone and the cross-section of stock returns

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  • Huang, Tao
  • Zhang, Xueyong

Abstract

This paper investigates the cross-sectional relation between industry-level media tone and expected stock returns in China. Using a machine learning technique to establish a proxy for industry-level media tone, we find that stocks in industries with more positive media tone earn significantly higher future returns than these with more negative media tone. Specifically, relative to stock-specific media tone, industry media tone plays a dominant role in forecasting stock returns. Moreover, the return premium for higher industry-level media tone continues for two months, and the returns are positive though insignificant within half a year, indicating that the media contains fundamental information.

Suggested Citation

  • Huang, Tao & Zhang, Xueyong, 2022. "Industry-level media tone and the cross-section of stock returns," International Review of Economics & Finance, Elsevier, vol. 77(C), pages 59-77.
    • Handle: RePEc:eee:reveco:v:77:y:2022:i:c:p:59-77
    DOI: 10.1016/j.iref.2021.09.002
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    1. 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.
    2. Calomiris, Charles W. & Mamaysky, Harry, 2019. "How news and its context drive risk and returns around the world," Journal of Financial Economics, Elsevier, vol. 133(2), pages 299-336.
    3. Tobias J. Moskowitz & Mark Grinblatt, 1999. "Do Industries Explain Momentum?," Journal of Finance, American Finance Association, vol. 54(4), pages 1249-1290, August.
    4. Merton, Robert C, 1987. "A Simple Model of Capital Market Equilibrium with Incomplete Information," Journal of Finance, American Finance Association, vol. 42(3), pages 483-510, July.
    5. Tsukioka, Yasutomo & Yanagi, Junya & Takada, Teruko, 2018. "Investor sentiment extracted from internet stock message boards and IPO puzzles," International Review of Economics & Finance, Elsevier, vol. 56(C), pages 205-217.
    6. Paul C. Tetlock, 2010. "Does Public Financial News Resolve Asymmetric Information?," The Review of Financial Studies, Society for Financial Studies, vol. 23(9), pages 3520-3557.
    7. Yugang Yin & Bin Tan, 2017. "Analyst’s ability, media selection and investor interests: evidence from China," China Finance Review International, Emerald Group Publishing Limited, vol. 7(1), pages 67-84, February.
    8. 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.
    9. Leung, Henry & Ton, Thai, 2015. "The impact of internet stock message boards on cross-sectional returns of small-capitalization stocks," Journal of Banking & Finance, Elsevier, vol. 55(C), pages 37-55.
    10. Peng, Lin & Xiong, Wei, 2006. "Investor attention, overconfidence and category learning," Journal of Financial Economics, Elsevier, vol. 80(3), pages 563-602, June.
    11. Hameed, Allaudeen & Mian, G. Mujtaba, 2015. "Industries and Stock Return Reversals," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 50(1-2), pages 89-117, April.
    12. Yanjian Zhu & Zhaoying Wu & Hua Zhang & Jing Yu, 2017. "Media sentiment, institutional investors and probability of stock price crash: evidence from Chinese stock markets," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 57(5), pages 1635-1670, December.
    13. Fama, Eugene F. & French, Kenneth R., 2015. "A five-factor asset pricing model," Journal of Financial Economics, Elsevier, vol. 116(1), pages 1-22.
    14. M. Cecilia Bustamante, 2015. "Editor's Choice Strategic Investment and Industry Risk Dynamics," The Review of Financial Studies, Society for Financial Studies, vol. 28(2), pages 297-341.
    15. Liu, Jianan & Stambaugh, Robert F. & Yuan, Yu, 2019. "Size and value in China," Journal of Financial Economics, Elsevier, vol. 134(1), pages 48-69.
    16. 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.
    17. 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.
    18. Fama, Eugene F & MacBeth, James D, 1973. "Risk, Return, and Equilibrium: Empirical Tests," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 607-636, May-June.
    19. Fang, Libing & Yu, Honghai & Huang, Yingbo, 2018. "The role of investor sentiment in the long-term correlation between U.S. stock and bond markets," International Review of Economics & Finance, Elsevier, vol. 58(C), pages 127-139.
    20. Fama, Eugene F & French, Kenneth R, 1992. "The Cross-Section of Expected Stock Returns," Journal of Finance, American Finance Association, vol. 47(2), pages 427-465, June.
    21. Siganos, Antonios & Vagenas-Nanos, Evangelos & Verwijmeren, Patrick, 2017. "Divergence of sentiment and stock market trading," Journal of Banking & Finance, Elsevier, vol. 78(C), pages 130-141.
    22. Dayong Dong & Keke Wu, 2019. "Investor attention is a risk pricing factor? Evidence from Chinese investors for self-selected stocks," China Finance Review International, Emerald Group Publishing Limited, vol. 10(1), pages 95-112, March.
    23. Sun, Licheng & Najand, Mohammad & Shen, Jiancheng, 2016. "Stock return predictability and investor sentiment: A high-frequency perspective," Journal of Banking & Finance, Elsevier, vol. 73(C), pages 147-164.
    24. Carhart, Mark M, 1997. "On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
    25. 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.
    26. Kewei Hou & David T. Robinson, 2006. "Industry Concentration and Average Stock Returns," Journal of Finance, American Finance Association, vol. 61(4), pages 1927-1956, August.
    27. Brad M. Barber & Terrance Odean, 2008. "All That Glitters: The Effect of Attention and News on the Buying Behavior of Individual and Institutional Investors," The Review of Financial Studies, Society for Financial Studies, vol. 21(2), pages 785-818, April.
    28. Robert Novy-Marx & Mihail Velikov, 2016. "A Taxonomy of Anomalies and Their Trading Costs," The Review of Financial Studies, Society for Financial Studies, vol. 29(1), pages 104-147.
    29. Andrew Detzel & Philipp Schaberl & Jack Strauss, 2019. "Expected versus Ex Post Profitability in the Cross‐Section of Industry Returns," Financial Management, Financial Management Association International, vol. 48(2), pages 505-536, June.
    30. 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.
    31. Sanjiv Sabherwal & Salil K. Sarkar & Ying Zhang, 2011. "Do Internet Stock Message Boards Influence Trading? Evidence from Heavily Discussed Stocks with No Fundamental News," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 38(9-10), pages 1209-1237, November.
    32. Hongquan Zhu & Lingling Jiang, 2017. "Investor recognition and stock returns: evidence from China," China Finance Review International, Emerald Group Publishing Limited, vol. 8(2), pages 199-215, December.
    33. 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.
    34. Joel Hasbrouck, 2009. "Trading Costs and Returns for U.S. Equities: Estimating Effective Costs from Daily Data," Journal of Finance, American Finance Association, vol. 64(3), pages 1445-1477, June.
    35. Alok Kumar & Charles M.C. Lee, 2006. "Retail Investor Sentiment and Return Comovements," Journal of Finance, American Finance Association, vol. 61(5), pages 2451-2486, October.
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    More about this item

    Keywords

    Media tone; Stock return; Industry; News; Investor sentiment;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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