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Asymmetric visibility of extreme past returns

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  • Bank, Matthias

Abstract

I use the maximum and minimum daily return of a stock in one month, as introduced by Bali et al. (2011), as a measure of the relative visibility of a stock. I argue that stocks that are essentially visible only as losers (winners) will have abnormally high (low) subsequent returns. My results are based on a sample of large US stocks (S&P 500 sample) and show that only asymmetric combinations of visibility produce statistically and economically significant excess returns.

Suggested Citation

  • Bank, Matthias, 2025. "Asymmetric visibility of extreme past returns," Finance Research Letters, Elsevier, vol. 83(C).
  • Handle: RePEc:eee:finlet:v:83:y:2025:i:c:s1544612325008281
    DOI: 10.1016/j.frl.2025.107569
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    References listed on IDEAS

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    1. Bali, Turan G. & Cakici, Nusret & Whitelaw, Robert F., 2011. "Maxing out: Stocks as lotteries and the cross-section of expected returns," Journal of Financial Economics, Elsevier, vol. 99(2), pages 427-446, February.
    2. Pedro Bordalo & Nicola Gennaioli & Andrei Shleifer, 2012. "Salience Theory of Choice Under Risk," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 127(3), pages 1243-1285.
    3. Pedro Bordalo & Nicola Gennaioli & Andrei Shleifer, 2013. "Salience and Asset Prices," American Economic Review, American Economic Association, vol. 103(3), pages 623-628, May.
    4. Carhart, Mark M, 1997. "On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
    5. Jegadeesh, Narasimhan, 1990. "Evidence of Predictable Behavior of Security Returns," Journal of Finance, American Finance Association, vol. 45(3), pages 881-898, July.
    6. Frazzini, Andrea & Pedersen, Lasse Heje, 2014. "Betting against beta," Journal of Financial Economics, Elsevier, vol. 111(1), pages 1-25.
    7. Malcolm Baker & Brendan Bradley & Jeffrey Wurgler, 2011. "Benchmarks as Limits to Arbitrage: Understanding the Low-Volatility Anomaly," Financial Analysts Journal, Taylor & Francis Journals, vol. 67(1), pages 40-54, January.
    8. 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.
    9. Peng, Lin & Xiong, Wei, 2006. "Investor attention, overconfidence and category learning," Journal of Financial Economics, Elsevier, vol. 80(3), pages 563-602, June.
    10. Fama, Eugene F. & French, Kenneth R., 2015. "A five-factor asset pricing model," Journal of Financial Economics, Elsevier, vol. 116(1), pages 1-22.
    11. Bloomfield, Robert & Libby, Robert & Nelson, Mark W., 2000. "Underreactions, overreactions and moderated confidence," Journal of Financial Markets, Elsevier, vol. 3(2), pages 113-137, May.
    12. Andrew Ang & Robert J. Hodrick & Yuhang Xing & Xiaoyan Zhang, 2006. "The Cross‐Section of Volatility and Expected Returns," Journal of Finance, American Finance Association, vol. 61(1), pages 259-299, February.
    13. Bruce N. Lehmann, 1990. "Fads, Martingales, and Market Efficiency," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 105(1), pages 1-28.
    14. 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.
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