IDEAS home Printed from https://ideas.repec.org/a/eee/reveco/v69y2020icp599-613.html
   My bibliography  Save this article

Preference for lottery features in real estate investment trusts

Author

Listed:
  • Zhu, Zhaobo
  • Harrison, DavidM.
  • Seiler, MichaelJ.

Abstract

This paper provides strong and novel evidence of the preference among investors for lottery-like payoffs by documenting a strong intra-industry MAX effect in REITs. Specifically, REITs with high maximum daily returns (high MAX) over the past 1-month significantly underperform REITs with low maximum daily returns (low MAX) over the same period. Such underperformance is persistent in subsequent months, although the underperformance is significant only in several months. In general, high MAX REITs are smaller and exhibit lower prices and higher idiosyncratic volatility than other REITs. However, firm characteristics cannot explain the MAX effect among REITs. In contrast, the MAX effect could significantly explain the idiosyncratic volatility puzzle among REITs. Moreover, the MAX effect is more pronounced among REITs with low institutional ownerships, while investor sentiment has no significant effect on the MAX effect among REITs.

Suggested Citation

  • Zhu, Zhaobo & Harrison, DavidM. & Seiler, MichaelJ., 2020. "Preference for lottery features in real estate investment trusts," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 599-613.
  • Handle: RePEc:eee:reveco:v:69:y:2020:i:c:p:599-613
    DOI: 10.1016/j.iref.2020.05.012
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1059056020301039
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.iref.2020.05.012?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Chui, Andy C. W. & Titman, Sheridan & Wei, K. C. John, 2003. "Intra-industry momentum: the case of REITs," Journal of Financial Markets, Elsevier, vol. 6(3), pages 363-387, May.
    2. 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.
    3. 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.
    4. Michael Cooper & David H. Downs, 1999. "Real Estate Securities and a Filter-based, Short-term Trading Strategy," Journal of Real Estate Research, American Real Estate Society, vol. 18(2), pages 313-334.
    5. 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.
    6. Tobias J. Moskowitz & Mark Grinblatt, 1999. "Do Industries Explain Momentum?," Journal of Finance, American Finance Association, vol. 54(4), pages 1249-1290, August.
    7. 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.
    8. Hameed, Allaudeen & Mian, G. Mujtaba, 2015. "Industries and Stock Return Reversals," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 50(1-2), pages 89-117, April.
    9. 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.
    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. 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.
    12. 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.
    13. Alok Kumar, 2009. "Who Gambles in the Stock Market?," Journal of Finance, American Finance Association, vol. 64(4), pages 1889-1933, August.
    14. Stambaugh, Robert F. & Yu, Jianfeng & Yuan, Yu, 2012. "The short of it: Investor sentiment and anomalies," Journal of Financial Economics, Elsevier, vol. 104(2), pages 288-302.
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    19. 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.
    20. 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.
    21. Joseph Ooi & Jingliang Wang & James Webb, 2009. "Idiosyncratic Risk and REIT Returns," The Journal of Real Estate Finance and Economics, Springer, vol. 38(4), pages 420-442, May.
    22. Carhart, Mark M, 1997. "On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
    23. Crystal Lin & Hamid Rahman & Kenneth Yung, 2009. "Investor Sentiment and REIT Returns," The Journal of Real Estate Finance and Economics, Springer, vol. 39(4), pages 450-471, November.
    24. R. Jared DeLisle & S. McKay Price & C.F. Sirmans, 2013. "Pricing of Volatility Risk in REITs," Journal of Real Estate Research, American Real Estate Society, vol. 35(2), pages 223-248.
    25. Zhi Da & Qianqiu Liu & Ernst Schaumburg, 2014. "A Closer Look at the Short-Term Return Reversal," Management Science, INFORMS, vol. 60(3), pages 658-674, March.
    26. Fong, Wai Mun & Toh, Benjamin, 2014. "Investor sentiment and the MAX effect," Journal of Banking & Finance, Elsevier, vol. 46(C), pages 190-201.
    27. Wan, Xiaoyuan, 2018. "Is the idiosyncratic volatility anomaly driven by the MAX or MIN effect? Evidence from the Chinese stock market," International Review of Economics & Finance, Elsevier, vol. 53(C), pages 1-15.
    28. Seif, Mostafa & Docherty, Paul & Shamsuddin, Abul, 2018. "Limits to arbitrage and the MAX anomaly in advanced emerging markets," Emerging Markets Review, Elsevier, vol. 36(C), pages 95-109.
    29. Miller, Edward M, 1977. "Risk, Uncertainty, and Divergence of Opinion," Journal of Finance, American Finance Association, vol. 32(4), pages 1151-1168, September.
    30. 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.
    31. 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.
    32. 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.
    33. Cheng, Si & Hameed, Allaudeen & Subrahmanyam, Avanidhar & Titman, Sheridan, 2017. "Short-Term Reversals: The Effects of Past Returns and Institutional Exits," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 52(1), pages 143-173, February.
    34. Nguyen, Hung T. & Truong, Cameron, 2018. "When are extreme daily returns not lottery? At earnings announcements!," Journal of Financial Markets, Elsevier, vol. 41(C), pages 92-116.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Xinyi Li & Yuhong Zhang & Xing Zhang & Runtang Gu, 2023. "Analyzing the Relationship between the Features of Direct Real Estate Assets and Their Corresponding Australian—REITs," IJFS, MDPI, vol. 11(1), pages 1-15, February.
    2. Melisa Ozdamar & Levent Akdeniz & Ahmet Sensoy, 2021. "Lottery-like preferences and the MAX effect in the cryptocurrency market," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-27, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Adam Zaremba & Jacob Koby Shemer, 2018. "Price-Based Investment Strategies," Springer Books, Springer, number 978-3-319-91530-2, September.
    2. 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.
    3. 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.
    4. Melisa Ozdamar & Levent Akdeniz & Ahmet Sensoy, 2021. "Lottery-like preferences and the MAX effect in the cryptocurrency market," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-27, December.
    5. Byun, Suk-Joon & Kim, Da-Hea, 2016. "Gambling preference and individual equity option returns," Journal of Financial Economics, Elsevier, vol. 122(1), pages 155-174.
    6. Cakici, Nusret & Zaremba, Adam, 2022. "Salience theory and the cross-section of stock returns: International and further evidence," Journal of Financial Economics, Elsevier, vol. 146(2), pages 689-725.
    7. Lin, Chaonan & Chen, Hong-Yi & Ko, Kuan-Cheng & Yang, Nien-Tzu, 2021. "Time-dependent lottery preference and the cross-section of stock returns," Journal of Empirical Finance, Elsevier, vol. 64(C), pages 272-294.
    8. Berggrun, Luis & Cardona, Emilio & Lizarzaburu, Edmundo, 2019. "Extreme daily returns and the cross-section of expected returns: Evidence from Brazil," Journal of Business Research, Elsevier, vol. 102(C), pages 201-211.
    9. Hsu, Ching-Chi & Chen, Miao-Ling, 2018. "Timing of advertising and the MAX effect," Journal of Behavioral and Experimental Finance, Elsevier, vol. 20(C), pages 105-114.
    10. Xu, Zhongxiang & Chevapatrakul, Thanaset & Li, Xiafei, 2019. "Return asymmetry and the cross section of stock returns," Journal of International Money and Finance, Elsevier, vol. 97(C), pages 93-110.
    11. Wan, Xiaoyuan, 2018. "Is the idiosyncratic volatility anomaly driven by the MAX or MIN effect? Evidence from the Chinese stock market," International Review of Economics & Finance, Elsevier, vol. 53(C), pages 1-15.
    12. Nguyen, Hung T. & Truong, Cameron, 2018. "When are extreme daily returns not lottery? At earnings announcements!," Journal of Financial Markets, Elsevier, vol. 41(C), pages 92-116.
    13. Yao, Shouyu & Wang, Chunfeng & Fang, Zhenming & Chiao, Chaoshin, 2021. "MAX is not the max under the interference of daily price limits: Evidence from China," International Review of Economics & Finance, Elsevier, vol. 73(C), pages 348-369.
    14. Goh, Jihoon & Jeong, Giho & Kang, Jangkoo, 2022. "The reference dependency of short-term reversal," International Review of Economics & Finance, Elsevier, vol. 78(C), pages 195-211.
    15. Cosemans, Mathijs & Frehen, Rik, 2021. "Salience theory and stock prices: Empirical evidence," Journal of Financial Economics, Elsevier, vol. 140(2), pages 460-483.
    16. Mei-Chen Lin, 2020. "When analysts encounter lottery-like stocks: lottery-like stocks and analyst stock recommendations," Review of Quantitative Finance and Accounting, Springer, vol. 55(1), pages 327-353, July.
    17. Lin, Mei-Chen & Lin, Yu-Ling, 2021. "Idiosyncratic skewness and cross-section of stock returns: Evidence from Taiwan," International Review of Financial Analysis, Elsevier, vol. 77(C).
    18. Atilgan, Yigit & Bali, Turan G. & Demirtas, K. Ozgur & Gunaydin, A. Doruk, 2020. "Left-tail momentum: Underreaction to bad news, costly arbitrage and equity returns," Journal of Financial Economics, Elsevier, vol. 135(3), pages 725-753.
    19. Cakici, Nusret & Zaremba, Adam, 2023. "Recency bias and the cross-section of international stock returns," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 84(C).
    20. Zhu, Hongbing & Yang, Lihua & Xu, Changxin, 2023. "Tracking investor gambling intensity," International Review of Financial Analysis, Elsevier, vol. 86(C).

    More about this item

    Keywords

    Lottery preference; MAX Effect; REITs;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • 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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:reveco:v:69:y:2020:i:c:p:599-613. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/620165 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.