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Can Sentiment Analysis and Options Volume Anticipate Future Returns?

Author

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  • Patrick Houlihan

    (Stevens Institute of Technology)

  • Germán G. Creamer

    (Stevens Institute of Technology)

Abstract

This paper evaluates the question of whether sentiment extracted from social media and options volume anticipates future asset return. The research utilized both textual based data and a particular market data derived call-put ratio, collected between July 2009 and September 2012. It shows that: (1) features derived from market data and a call-put ratio can improve model performance, (2) sentiment derived from StockTwits, a social media platform for the financial community, further enhances model performance, (3) aggregating all features together also facilitates performance, and (4) sentiment from social media and market data can be used as risk factors in an asset pricing framework.

Suggested Citation

  • Patrick Houlihan & Germán G. Creamer, 2017. "Can Sentiment Analysis and Options Volume Anticipate Future Returns?," Computational Economics, Springer;Society for Computational Economics, vol. 50(4), pages 669-685, December.
    • Handle: RePEc:kap:compec:v:50:y:2017:i:4:d:10.1007_s10614-017-9694-4
    DOI: 10.1007/s10614-017-9694-4
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    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. De Long, J Bradford, et al, 1990. "Positive Feedback Investment Strategies and Destabilizing Rational Speculation," Journal of Finance, American Finance Association, vol. 45(2), pages 379-395, June.
    3. Hamid, Alain & Heiden, Moritz, 2015. "Forecasting volatility with empirical similarity and Google Trends," Journal of Economic Behavior & Organization, Elsevier, vol. 117(C), pages 62-81.
    4. Danbolt, Jo & Siganos, Antonios & Vagenas-Nanos, Evangelos, 2015. "Investor sentiment and bidder announcement abnormal returns," Journal of Corporate Finance, Elsevier, vol. 33(C), pages 164-179.
    5. 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.
    6. Zhang, Wei & Shen, Dehua & Zhang, Yongjie & Xiong, Xiong, 2013. "Open source information, investor attention, and asset pricing," Economic Modelling, Elsevier, vol. 33(C), pages 613-619.
    7. Zhi Da & Joseph Engelberg & Pengjie Gao, 2011. "In Search of Attention," Journal of Finance, American Finance Association, vol. 66(5), pages 1461-1499, October.
    8. 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.
    9. Carhart, Mark M, 1997. "On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
    10. 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.
    11. 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.
    12. Charles Cao & Zhiwu Chen & John M. Griffin, 2005. "Informational Content of Option Volume Prior to Takeovers," The Journal of Business, University of Chicago Press, vol. 78(3), pages 1073-1109, May.
    13. Kaplan, Andreas M. & Haenlein, Michael, 2010. "Users of the world, unite! The challenges and opportunities of Social Media," Business Horizons, Elsevier, vol. 53(1), pages 59-68, January.
    14. repec:bla:jfinan:v:43:y:1988:i:4:p:949-64 is not listed on IDEAS
    15. Shen, Dehua & Zhang, Wei & Xiong, Xiong & Li, Xiao & Zhang, Yongjie, 2016. "Trading and non-trading period Internet information flow and intraday return volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 451(C), pages 519-524.
    16. 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.
    17. Zhang, Yongjie & Feng, Lina & Jin, Xi & Shen, Dehua & Xiong, Xiong & Zhang, Wei, 2014. "Internet information arrival and volatility of SME PRICE INDEX," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 399(C), pages 70-74.
    18. repec:bla:jfinan:v:59:y:2004:i:3:p:1259-1294 is not listed on IDEAS
    19. Michael H. Breitner & Christian Dunis & Hans-Jörg Mettenheim & Christopher Neely & Georgios Sermpinis & Azizah Abu Bakar & Antonios Siganos & Evangelos Vagenas‐Nanos, 2014. "Does Mood Explain the Monday Effect?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(6), pages 409-418, September.
    20. Kim, Soon-Ho & Kim, Dongcheol, 2014. "Investor sentiment from internet message postings and the predictability of stock returns," Journal of Economic Behavior & Organization, Elsevier, vol. 107(PB), pages 708-729.
    21. 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.
    22. Hu, Jianfeng, 2014. "Does option trading convey stock price information?," Journal of Financial Economics, Elsevier, vol. 111(3), pages 625-645.
    23. 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.
    24. Chen, Zhuo & Lu, Andrea, 2017. "Slow diffusion of information and price momentum in stocks: Evidence from options markets," Journal of Banking & Finance, Elsevier, vol. 75(C), pages 98-108.
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    2. Meng‐Feng Yen & Yu‐Pei Huang & Liang‐Chih Yu & Yueh‐Ling Chen, 2022. "A Two-Dimensional Sentiment Analysis of Online Public Opinion and Future Financial Performance of Publicly Listed Companies," Computational Economics, Springer;Society for Computational Economics, vol. 59(4), pages 1677-1698, April.

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