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Quantifying the cross sectional relation of daily happiness sentiment and return skewness: Evidence from US industries

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  • Zhao, Ruwei

Abstract

In this paper, we initiate cross-sectional return skewness correlation study between investor daily happiness sentiment (DHS) and twenty-two US industry indices. The Twitter happiness index, originated from the world’s largest microblog platform, Twitter.com, is employed as the representative of DHS. Also, with quantile setting of DHS, we break our full sample into five subsamples and detect apparent and reliable skewness distinctions among DHS subgroups. We further implement the robustness check with altered subgroups for the credibility enhancement. In summary, the robustness results follow the steps of original findings.

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  • Zhao, Ruwei, 2020. "Quantifying the cross sectional relation of daily happiness sentiment and return skewness: Evidence from US industries," Journal of Behavioral and Experimental Finance, Elsevier, vol. 27(C).
    • Handle: RePEc:eee:beexfi:v:27:y:2020:i:c:s2214635020300873
    DOI: 10.1016/j.jbef.2020.100369
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    as
    1. 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.
    2. Mehra, Rajnish & Prescott, Edward C., 1985. "The equity premium: A puzzle," Journal of Monetary Economics, Elsevier, vol. 15(2), pages 145-161, March.
    3. Cadsby, Charles Bram & Ratner, Mitchell, 1992. "Turn-of-month and pre-holiday effects on stock returns: Some international evidence," Journal of Banking & Finance, Elsevier, vol. 16(3), pages 497-509, June.
    4. Fama, Eugene F., 1998. "Market efficiency, long-term returns, and behavioral finance," Journal of Financial Economics, Elsevier, vol. 49(3), pages 283-306, September.
    5. Li, Xiao & Shen, Dehua & Zhang, Wei, 2018. "Do Chinese internet stock message boards convey firm-specific information?," Pacific-Basin Finance Journal, Elsevier, vol. 49(C), pages 1-14.
    6. Norman Strong & Xinzhong Xu, 2003. "Understanding the Equity Home Bias: Evidence from Survey Data," The Review of Economics and Statistics, MIT Press, vol. 85(2), pages 307-312, May.
    7. Reinganum, Marc R., 1983. "The anomalous stock market behavior of small firms in January : Empirical tests for tax-loss selling effects," Journal of Financial Economics, Elsevier, vol. 12(1), pages 89-104, June.
    8. Zhao, Ruwei & Xiong, Xiong & Shen, Dehua, 2018. "Investor attention and performance of IPO firms: Evidence from online searches," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 342-348.
    9. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    10. De Bondt, Werner F M & Thaler, Richard, 1985. "Does the Stock Market Overreact?," Journal of Finance, American Finance Association, vol. 40(3), pages 793-805, July.
    11. Zhang, Zuochao & Zhang, Yongjie & Shen, Dehua & Zhang, Wei, 2018. "The cross-correlations between online sentiment proxies: Evidence from Google Trends and Twitter," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 67-75.
    12. Shen, Dehua & Liu, Lanbiao & Zhang, Yongjie, 2018. "Quantifying the cross-sectional relationship between online sentiment and the skewness of stock returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 928-934.
    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. Lei Feng & Mark Seasholes, 2005. "Do Investor Sophistication and Trading Experience Eliminate Behavioral Biases in Financial Markets?," Review of Finance, Springer, vol. 9(3), pages 305-351, September.
    15. 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.
    16. Kunkel, Robert A. & Compton, William S. & Beyer, Scott, 2003. "The turn-of-the-month effect still lives: the international evidence," International Review of Financial Analysis, Elsevier, vol. 12(2), pages 207-221.
    17. Li, Xiao & Shen, Dehua & Xue, Mei & Zhang, Wei, 2017. "Daily happiness and stock returns: The case of Chinese company listed in the United States," Economic Modelling, Elsevier, vol. 64(C), pages 496-501.
    18. 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.
    19. Zuochao Zhang & Yongjie Zhang & Dehua Shen & Wei Zhang, 2018. "The Dynamic Cross-Correlations between Mass Media News, New Media News, and Stock Returns," Complexity, Hindawi, vol. 2018, pages 1-11, February.
    20. 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.
    21. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    22. Lee, Charles M C & Shleifer, Andrei & Thaler, Richard H, 1991. "Investor Sentiment and the Closed-End Fund Puzzle," Journal of Finance, American Finance Association, vol. 46(1), pages 75-109, March.
    23. Shefrin, Hersh & Statman, Meir, 1985. "The Disposition to Sell Winners Too Early and Ride Losers Too Long: Theory and Evidence," Journal of Finance, American Finance Association, vol. 40(3), pages 777-790, July.
    24. 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.
    25. Shen, Dehua & Li, Xiao & Zhang, Wei, 2017. "Baidu news coverage and its impacts on order imbalance and large-size trade of Chinese stocks," Finance Research Letters, Elsevier, vol. 23(C), pages 210-216.
    26. John A. List, 2003. "Does Market Experience Eliminate Market Anomalies?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 118(1), pages 41-71.
    27. French, Kenneth R., 1980. "Stock returns and the weekend effect," Journal of Financial Economics, Elsevier, vol. 8(1), pages 55-69, March.
    28. Sven Bouman & Ben Jacobsen, 2002. "The Halloween Indicator, "Sell in May and Go Away": Another Puzzle," American Economic Review, American Economic Association, vol. 92(5), pages 1618-1635, December.
    29. Lei Feng & Mark S. Seasholes, 2005. "Do Investor Sophistication and Trading Experience Eliminate Behavioral Biases in Financial Markets?," Review of Finance, European Finance Association, vol. 9(3), pages 305-351.
    30. Shen, Dehua & Li, Xiao & Zhang, Wei, 2018. "Baidu news information flow and return volatility: Evidence for the Sequential Information Arrival Hypothesis," Economic Modelling, Elsevier, vol. 69(C), pages 127-133.
    31. Ariel, Robert A, 1990. "High Stock Returns before Holidays: Existence and Evidence on Possible Causes," Journal of Finance, American Finance Association, vol. 45(5), pages 1611-1626, December.
    32. Fama, Eugene F, 1991. "Efficient Capital Markets: II," Journal of Finance, American Finance Association, vol. 46(5), pages 1575-1617, December.
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    Cited by:

    1. Yousaf, Imran & Youssef, Manel & Goodell, John W., 2022. "Quantile connectedness between sentiment and financial markets: Evidence from the S&P 500 twitter sentiment index," International Review of Financial Analysis, Elsevier, vol. 83(C).
    2. Byström, Hans, 2020. "Happiness and Gold Prices," Finance Research Letters, Elsevier, vol. 35(C).
    3. Naeem, Muhammad Abubakr & Farid, Saqib & Faruk, Balli & Shahzad, Syed Jawad Hussain, 2020. "Can happiness predict future volatility in stock markets?," Research in International Business and Finance, Elsevier, vol. 54(C).
    4. Chen, Qitong & Zhu, Huiming & Yu, Dongwei & Hau, Liya, 2022. "How does investor attention matter for crude oil prices and returns? Evidence from time-frequency quantile causality analysis," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
    5. Văn, Lê & Bảo, Nguyễn Khắc Quốc, 2022. "The relationship between global stock and precious metals under Covid-19 and happiness perspectives," Resources Policy, Elsevier, vol. 77(C).
    6. Chen, Wen-Yi & Chen, Mei-Ping, 2022. "Twitter’s daily happiness sentiment, economic policy uncertainty, and stock index fluctuations," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    7. Li, Yue & W. Goodell, John & Shen, Dehua, 2021. "Does happiness forecast implied volatility? Evidence from nonparametric wave-based Granger causality testing," The Quarterly Review of Economics and Finance, Elsevier, vol. 81(C), pages 113-122.

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    More about this item

    Keywords

    Twitter happiness index; US industry indices; Quantile setting; Cross sectional comparison;
    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

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