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Media-expressed tone, Option Characteristics, and Stock Return Predictability

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  • Chen, Cathy Yi-Hsuan
  • Fengler, Matthias R.
  • Härdle, Wolfgang Karl
  • Liu, Yanchu

Abstract

We distill tone from a huge assortment of NASDAQ articles to examine the predictive power of media-expressed tone in single-stock option markets and equity markets. We find that (1) option markets are impacted by media tone; (2) option variables predict stock returns along with tone; (3) option variables orthogonalized to public information and tone are more effective predictors of stock returns; (4) overnight tone appears to be more informative than trading- time tone, possibly due to a different thematic coverage of the trading versus the overnight archive; (5) tone disagreement commands a strong positive risk premium above and beyond market volatility.

Suggested Citation

  • Chen, Cathy Yi-Hsuan & Fengler, Matthias R. & Härdle, Wolfgang Karl & Liu, Yanchu, 2019. "Media-expressed tone, Option Characteristics, and Stock Return Predictability," IRTG 1792 Discussion Papers 2019-015, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    • Handle: RePEc:zbw:irtgdp:2019015
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    as
    1. Jun Pan & Allen M. Poteshman, 2006. "The Information in Option Volume for Future Stock Prices," The Review of Financial Studies, Society for Financial Studies, vol. 19(3), pages 871-908.
    2. Harrison Hong & Terence Lim & Jeremy C. Stein, 2000. "Bad News Travels Slowly: Size, Analyst Coverage, and the Profitability of Momentum Strategies," Journal of Finance, American Finance Association, vol. 55(1), pages 265-295, February.
    3. Chang, Bo Young & Christoffersen, Peter & Jacobs, Kris, 2013. "Market skewness risk and the cross section of stock returns," Journal of Financial Economics, Elsevier, vol. 107(1), pages 46-68.
    4. Miller, Edward M, 1977. "Risk, Uncertainty, and Divergence of Opinion," Journal of Finance, American Finance Association, vol. 32(4), pages 1151-1168, September.
    5. Dennis, Patrick & Mayhew, Stewart, 2002. "Risk-Neutral Skewness: Evidence from Stock Options," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 37(3), pages 471-493, September.
    6. 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.
    7. 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.
    8. Buncic, Daniel & Gisler, Katja I.M., 2016. "Global equity market volatility spillovers: A broader role for the United States," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1317-1339.
    9. Henk Berkman & Cameron Truong, 2009. "Event Day 0? After‐Hours Earnings Announcements," Journal of Accounting Research, Wiley Blackwell, vol. 47(1), pages 71-103, March.
    10. Tim Loughran & Bill Mcdonald, 2016. "Textual Analysis in Accounting and Finance: A Survey," Journal of Accounting Research, Wiley Blackwell, vol. 54(4), pages 1187-1230, September.
    11. Sanderson, Eleanor & Windmeijer, Frank, 2016. "A weak instrument F-test in linear IV models with multiple endogenous variables," Journal of Econometrics, Elsevier, vol. 190(2), pages 212-221.
    12. Kleibergen, Frank & Paap, Richard, 2006. "Generalized reduced rank tests using the singular value decomposition," Journal of Econometrics, Elsevier, vol. 133(1), pages 97-126, July.
    13. H. Henry Cao & Joshua D. Coval & David Hirshleifer, 2002. "Sidelined Investors, Trading-Generated News, and Security Returns," The Review of Financial Studies, Society for Financial Studies, vol. 15(2), pages 615-648, March.
    14. 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.
    15. Kewei Hou & Tobias J. Moskowitz, 2005. "Market Frictions, Price Delay, and the Cross-Section of Expected Returns," The Review of Financial Studies, Society for Financial Studies, vol. 18(3), pages 981-1020.
    16. 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.
    17. Engelberg, Joseph E. & Reed, Adam V. & Ringgenberg, Matthew C., 2012. "How are shorts informed?," Journal of Financial Economics, Elsevier, vol. 105(2), pages 260-278.
    18. Sibley, Steven E. & Wang, Yanchu & Xing, Yuhang & Zhang, Xiaoyan, 2016. "The information content of the sentiment index," Journal of Banking & Finance, Elsevier, vol. 62(C), pages 164-179.
    19. Lior Menzly & Oguzhan Ozbas, 2010. "Market Segmentation and Cross‐predictability of Returns," Journal of Finance, American Finance Association, vol. 65(4), pages 1555-1580, August.
    20. Jennifer Conrad & Robert F. Dittmar & Eric Ghysels, 2013. "Ex Ante Skewness and Expected Stock Returns," Journal of Finance, American Finance Association, vol. 68(1), pages 85-124, February.
    21. Larsen, Vegard H. & Thorsrud, Leif Anders & Zhulanova, Julia, 2021. "News-driven inflation expectations and information rigidities," Journal of Monetary Economics, Elsevier, vol. 117(C), pages 507-520.
    22. 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.
    23. repec:bla:jfinan:v:59:y:2004:i:3:p:1259-1294 is not listed on IDEAS
    24. Bollerslev, Tim & Osterrieder, Daniela & Sizova, Natalia & Tauchen, George, 2013. "Risk and return: Long-run relations, fractional cointegration, and return predictability," Journal of Financial Economics, Elsevier, vol. 108(2), pages 409-424.
    25. Carlin, Bruce I. & Longstaff, Francis A. & Matoba, Kyle, 2014. "Disagreement and asset prices," Journal of Financial Economics, Elsevier, vol. 114(2), pages 226-238.
    26. Moshirian, Fariborz & Nguyen, Huong Giang (Lily) & Pham, Peter Kien, 2012. "Overnight public information, order placement, and price discovery during the pre-opening period," Journal of Banking & Finance, Elsevier, vol. 36(10), pages 2837-2851.
    27. 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.
    28. Stambaugh, Robert F. & Yu, Jianfeng & Yuan, Yu, 2012. "The short of it: Investor sentiment and anomalies," Journal of Financial Economics, Elsevier, vol. 104(2), pages 288-302.
    29. Paul C. Tetlock, 2011. "All the News That's Fit to Reprint: Do Investors React to Stale Information?," The Review of Financial Studies, Society for Financial Studies, vol. 24(5), pages 1481-1512.
    30. Douglas Staiger & James H. Stock, 1997. "Instrumental Variables Regression with Weak Instruments," Econometrica, Econometric Society, vol. 65(3), pages 557-586, May.
    31. Chen, Cathy Yi-Hsuan & Chiang, Thomas C. & Härdle, Wolfgang Karl, 2018. "Downside risk and stock returns in the G7 countries: An empirical analysis of their long-run and short-run dynamics," Journal of Banking & Finance, Elsevier, vol. 93(C), pages 21-32.
    32. Wang, Xunxiao & Wu, Chongfeng & Xu, Weidong, 2015. "Volatility forecasting: The role of lunch-break returns, overnight returns, trading volume and leverage effects," International Journal of Forecasting, Elsevier, vol. 31(3), pages 609-619.
    33. Xing, Yuhang & Zhang, Xiaoyan & Zhao, Rui, 2010. "What Does the Individual Option Volatility Smirk Tell Us About Future Equity Returns?," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 45(3), pages 641-662, June.
    34. Kim, Jun Sik & Ryu, Doojin & Seo, Sung Won, 2014. "Investor sentiment and return predictability of disagreement," Journal of Banking & Finance, Elsevier, vol. 42(C), pages 166-178.
    35. David Hirshleifer & Sonya S. Lim & Siew Hong Teoh, 2011. "Limited Investor Attention and Stock Market Misreactions to Accounting Information," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 1(1), pages 35-73.
    36. Michael J. Barclay, 2003. "Price Discovery and Trading After Hours," The Review of Financial Studies, Society for Financial Studies, vol. 16(4), pages 1041-1073.
    37. repec:bla:jfinan:v:59:y:2004:i:3:p:1235-1258 is not listed on IDEAS
    38. Diamond, Douglas W. & Verrecchia, Robert E., 1987. "Constraints on short-selling and asset price adjustment to private information," Journal of Financial Economics, Elsevier, vol. 18(2), pages 277-311, June.
    39. 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.
    40. Nerissa C. Brown & Richard M. Crowley & W. Brooke Elliott, 2020. "What Are You Saying? Using topic to Detect Financial Misreporting," Journal of Accounting Research, Wiley Blackwell, vol. 58(1), pages 237-291, March.
    41. Hailiang Chen & Prabuddha De & Yu (Jeffrey) Hu & Byoung-Hyoun Hwang, 2014. "Wisdom of Crowds: The Value of Stock Opinions Transmitted Through Social Media," The Review of Financial Studies, Society for Financial Studies, vol. 27(5), pages 1367-1403.
    42. Jacob Boudoukh & Ronen Feldman & Shimon Kogan & Matthew Richardson, 2019. "Information, Trading, and Volatility: Evidence from Firm-Specific News," The Review of Financial Studies, Society for Financial Studies, vol. 32(3), pages 992-1033.
    43. Pekka Malo & Ankur Sinha & Pekka Korhonen & Jyrki Wallenius & Pyry Takala, 2014. "Good debt or bad debt: Detecting semantic orientations in economic texts," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(4), pages 782-796, April.
    44. Alexander David, 2008. "Heterogeneous Beliefs, Speculation, and the Equity Premium," Journal of Finance, American Finance Association, vol. 63(1), pages 41-83, February.
    45. Yang Bao & Anindya Datta, 2014. "Simultaneously Discovering and Quantifying Risk Types from Textual Risk Disclosures," Management Science, INFORMS, vol. 60(6), pages 1371-1391, June.
    46. Elyasiani, Elyas & Mansur, Iqbal & Odusami, Babatunde, 2011. "Oil price shocks and industry stock returns," Energy Economics, Elsevier, vol. 33(5), pages 966-974, September.
    47. Bing Han, 2008. "Investor Sentiment and Option Prices," The Review of Financial Studies, Society for Financial Studies, vol. 21(1), pages 387-414, January.
    48. Cheolbeom Park, 2005. "Stock Return Predictability and the Dispersion in Earnings Forecasts," The Journal of Business, University of Chicago Press, vol. 78(6), pages 2351-2376, November.
    49. 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.
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    2. Chen, Chung-Chi & Huang, Yu-Lieh & Yang, Fang, 2024. "Semantics matter: An empirical study on economic policy uncertainty index," International Review of Economics & Finance, Elsevier, vol. 89(PA), pages 1286-1302.

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    More about this item

    Keywords

    option markets; equity markets; stock return predictability; media tone; topic model;
    All these keywords.

    JEL classification:

    • 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
    • G41 - Financial Economics - - Behavioral Finance - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making in Financial Markets

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