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Pre-earnings announcement returns and momentum

Author

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  • Jain, Archana
  • Jain, Chinmay
  • Khanapure, Revansiddha Basavaraj

Abstract

The trading strategy of buying winners and selling losers based on returns prior to earnings announcements is profitable with mean returns of 0.58%–0.64% per month. The equal-weighted version of this strategy is not spanned by 4-factor Fama–French model.

Suggested Citation

  • Jain, Archana & Jain, Chinmay & Khanapure, Revansiddha Basavaraj, 2020. "Pre-earnings announcement returns and momentum," Economics Letters, Elsevier, vol. 196(C).
    • Handle: RePEc:eee:ecolet:v:196:y:2020:i:c:s0165176520303177
    DOI: 10.1016/j.econlet.2020.109521
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    References listed on IDEAS

    as
    1. Obrien, Pc & Bhushan, R, 1990. "Analyst Following And Institutional Ownership," Journal of Accounting Research, Wiley Blackwell, vol. 28, pages 55-76.
    2. Jacob Thomas & Frank Zhang, 2008. "Overreaction to Intra‐industry Information Transfers?," Journal of Accounting Research, Wiley Blackwell, vol. 46(4), pages 909-940, September.
    3. Grinblatt, Mark & Han, Bing, 2005. "Prospect theory, mental accounting, and momentum," Journal of Financial Economics, Elsevier, vol. 78(2), pages 311-339, November.
    4. Thomas J. George & Chuan-Yang Hwang, 2004. "The 52-Week High and Momentum Investing," Journal of Finance, American Finance Association, vol. 59(5), pages 2145-2176, October.
    5. Andy C.W. Chui & Sheridan Titman & K.C. John Wei, 2010. "Individualism and Momentum around the World," Journal of Finance, American Finance Association, vol. 65(1), pages 361-392, February.
    6. Freeman, Robert & Tse, Senyo, 1992. "An earnings prediction approach to examining intercompany information transfers," Journal of Accounting and Economics, Elsevier, vol. 15(4), pages 509-523, December.
    7. Yu, Fang (Frank), 2008. "Analyst coverage and earnings management," Journal of Financial Economics, Elsevier, vol. 88(2), pages 245-271, May.
    8. Kumar, Alok, 2009. "Hard-to-Value Stocks, Behavioral Biases, and Informed Trading," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 44(6), pages 1375-1401, December.
    9. Jegadeesh, Narasimhan & Titman, Sheridan, 1993. "Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency," Journal of Finance, American Finance Association, vol. 48(1), pages 65-91, March.
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    Cited by:

    1. Yao, Shouyu & Qin, Yuanyuan & Cheng, Feiyang & Wu, Ji(George) & Goodell, John.W., 2022. "Missing momentum in China: Considering individual investor preference," Finance Research Letters, Elsevier, vol. 49(C).

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    More about this item

    Keywords

    Behavioral finance; Momentum; Earnings;
    All these keywords.

    JEL classification:

    • G4 - Financial Economics - - Behavioral Finance
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G30 - Financial Economics - - Corporate Finance and Governance - - - General

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