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Maxing out: the puzzling influence of past maximum returns on future asset prices in a cross-country analysis

Author

Listed:
  • Shuonan Yuan

    (Xi’an Polytechnic University)

  • Marc Oliver Rieger

    (University of Trier)

  • Nilüfer Caliskan

    (Kieger Wealth and Asset Management)

Abstract

We examine the role of extreme positive returns in the cross-section of stock returns in seven countries. While Bali et al. (J Financ Econ 99:427–446, 2011) find a significantly negative relation between the maximum daily returns over the past month (MAX) and the expected returns in the following month, we find that this relation disappears and even often reverses. The positive relation is found in Canada, the UK and the US, while the pattern in China is more in line with the previous findings, and for Germany, France and Japan the effect is not statistically significant. Further evidence using the US data suggests that the positive effect of MAX is largely a proxy for the idiosyncratic volatility. Moreover, we find that the MAX effect is mainly concentrated on periods before 1990’s given the same dataset as Bali et al. (2011). Collectively, our results indicate that the MAX effect is not stable over time. We conjecture the changing proportion of MAX-seeking investors is a crucial determinant of the MAX-return relation.

Suggested Citation

  • Shuonan Yuan & Marc Oliver Rieger & Nilüfer Caliskan, 2020. "Maxing out: the puzzling influence of past maximum returns on future asset prices in a cross-country analysis," Management Review Quarterly, Springer, vol. 70(4), pages 567-589, November.
    • Handle: RePEc:spr:manrev:v:70:y:2020:i:4:d:10.1007_s11301-019-00176-3
    DOI: 10.1007/s11301-019-00176-3
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    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. Markus K. Brunnermeier & Jonathan A. Parker & Christian Gollier, 2007. "Optimal Beliefs, Asset Prices, and the Preference for Skewed Returns," American Economic Review, American Economic Association, vol. 97(2), pages 159-165, May.
    3. Xiaoquan Jiang & Bong‐Soo Lee, 2006. "The Dynamic Relation Between Returns and Idiosyncratic Volatility," Financial Management, Financial Management Association International, vol. 35(2), pages 43-65, June.
    4. 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.
    5. John Y. Campbell & Martin Lettau & Burton G. Malkiel & Yexiao Xu, 2001. "Have Individual Stocks Become More Volatile? An Empirical Exploration of Idiosyncratic Risk," Journal of Finance, American Finance Association, vol. 56(1), pages 1-43, February.
    6. Jungshik Hur & Vivek Singh, 2017. "Cross-Section of Expected Returns and Extreme Returns: The Role of Investor Attention and Risk Preferences," Financial Management, Financial Management Association International, vol. 46(2), pages 409-431, June.
    7. Ang, Andrew & Hodrick, Robert J. & Xing, Yuhang & Zhang, Xiaoyan, 2009. "High idiosyncratic volatility and low returns: International and further U.S. evidence," Journal of Financial Economics, Elsevier, vol. 91(1), pages 1-23, January.
    8. Nartea, Gilbert V. & Kong, Dongmin & Wu, Ji, 2017. "Do extreme returns matter in emerging markets? Evidence from the Chinese stock market," Journal of Banking & Finance, Elsevier, vol. 76(C), pages 189-197.
    9. Han, Bing & Kumar, Alok, 2013. "Speculative Retail Trading and Asset Prices," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 48(2), pages 377-404, April.
    10. Amihud, Yakov, 2002. "Illiquidity and stock returns: cross-section and time-series effects," Journal of Financial Markets, Elsevier, vol. 5(1), pages 31-56, January.
    11. Fama, Eugene F. & French, Kenneth R., 2015. "A five-factor asset pricing model," Journal of Financial Economics, Elsevier, vol. 116(1), pages 1-22.
    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. 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. Tversky, Amos & Kahneman, Daniel, 1992. "Advances in Prospect Theory: Cumulative Representation of Uncertainty," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 297-323, October.
    15. Yong-Ho Cheon & Kuan-Hui Lee, 2018. "Maxing Out Globally: Individualism, Investor Attention, and the Cross Section of Expected Stock Returns," Management Science, INFORMS, vol. 64(12), pages 5807-5831, December.
    16. 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.
    17. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    18. Xiaoquan Jiang & Bong-Soo Lee, 2006. "The Dynamic Relation Between Returns and Idiosyncratic Volatility," Financial Management, Financial Management Association, vol. 35(2), Summer.
    19. Wai Mun Fong, 2014. "The MAX Effect," Palgrave Macmillan Books, in: The Lottery Mindset: Investors, Gambling and the Stock Market, chapter 7, pages 138-155, Palgrave Macmillan.
    20. Merton, Robert C, 1987. "A Simple Model of Capital Market Equilibrium with Incomplete Information," Journal of Finance, American Finance Association, vol. 42(3), pages 483-510, July.
    21. Nicholas Barberis & Ming Huang, 2008. "Stocks as Lotteries: The Implications of Probability Weighting for Security Prices," American Economic Review, American Economic Association, vol. 98(5), pages 2066-2100, December.
    22. Nicholas Barberis & Ming Huang, 2001. "Mental Accounting, Loss Aversion, and Individual Stock Returns," Journal of Finance, American Finance Association, vol. 56(4), pages 1247-1292, August.
    23. Zhong, Angel & Gray, Philip, 2016. "The MAX effect: An exploration of risk and mispricing explanations," Journal of Banking & Finance, Elsevier, vol. 65(C), pages 76-90.
    24. Todd Mitton & Keith Vorkink, 2007. "Equilibrium Underdiversification and the Preference for Skewness," The Review of Financial Studies, Society for Financial Studies, vol. 20(4), pages 1255-1288.
    25. Alok Kumar, 2009. "Who Gambles in the Stock Market?," Journal of Finance, American Finance Association, vol. 64(4), pages 1889-1933, August.
    26. 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.
    27. Annaert, Jan & De Ceuster, Marc & Verstegen, Kurt, 2013. "Are extreme returns priced in the stock market? European evidence," Journal of Banking & Finance, Elsevier, vol. 37(9), pages 3401-3411.
    28. Nicholas Barberis & Ming Huang, 2001. "Mental Accounting, Loss Aversion, and Individual Stock Returns," NBER Working Papers 8190, National Bureau of Economic Research, Inc.
    29. Terrance Odean, 1999. "Do Investors Trade Too Much?," American Economic Review, American Economic Association, vol. 89(5), pages 1279-1298, December.
    30. Fu, Fangjian, 2009. "Idiosyncratic risk and the cross-section of expected stock returns," Journal of Financial Economics, Elsevier, vol. 91(1), pages 24-37, January.
    31. Campbell R. Harvey & Akhtar Siddique, 2000. "Conditional Skewness in Asset Pricing Tests," Journal of Finance, American Finance Association, vol. 55(3), pages 1263-1295, June.
    32. Fong, Wai Mun & Toh, Benjamin, 2014. "Investor sentiment and the MAX effect," Journal of Banking & Finance, Elsevier, vol. 46(C), pages 190-201.
    33. Levy, Haim, 1978. "Equilibrium in an Imperfect Market: A Constraint on the Number of Securities in the Portfolio," American Economic Review, American Economic Association, vol. 68(4), pages 643-658, September.
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    More about this item

    Keywords

    Extreme positive returns; Cross-sectional returns; Factor-model; Idiosyncratic volatility;
    All these keywords.

    JEL classification:

    • G4 - Financial Economics - - Behavioral Finance
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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