IDEAS home Printed from https://ideas.repec.org/a/mof/journl/ppr022a.html
   My bibliography  Save this article

A Behavioral Economics Exploration into the "Volatility Anomaly" ``

Author

Listed:
  • Seiichiro Iwasawa

    (The NUCB Graduate School)

  • Tomonori Uchiyama

    (Equity Quantitative Research Department, Nomura Securities Co., Ltd.)

Abstract

Contrary to a commonsense view in traditional finance theories to the effect that expected returns on investments in high-risk securities are higher than those in low-risk investments, in the actual stock market, there are negative correlations, respectively, between the beta value of individual securities measured beforehand and the actual returns realized later, and between the idiosyncratic volatility measured beforehand and the actual returns realized later. Here we, based upon the empirical studies of investor behaviors in the Japanese stock market, present the fact that, behind the gbeta anomaly, h there is a preference for high-beta securities by typical institutional investors whose mandate is to beat a benchmark, and also that, behind the gidiosyncratic volatility anomaly, h there is a preference for positively skewed securities by individual investors, especially those engaged in margin trading, who overweight low tail probabilities assigned to the state of the world in which they make a lot of money by investing in the positively skewed stock, which could be called a ggambling preference. h

Suggested Citation

  • Seiichiro Iwasawa & Tomonori Uchiyama, 2013. "A Behavioral Economics Exploration into the "Volatility Anomaly" ``," Public Policy Review, Policy Research Institute, Ministry of Finance Japan, vol. 9(3), pages 457-490, September.
  • Handle: RePEc:mof:journl:ppr022a
    as

    Download full text from publisher

    File URL: http://warp.da.ndl.go.jp/info:ndljp/pid/11217434/www.mof.go.jp/english/pri/publication/pp_review/ppr022/ppr022a.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Thompson, Samuel B., 2011. "Simple formulas for standard errors that cluster by both firm and time," Journal of Financial Economics, Elsevier, vol. 99(1), pages 1-10, January.
    2. 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.
    3. 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.
    4. Chen, Joseph & Hong, Harrison & Stein, Jeremy C., 2001. "Forecasting crashes: trading volume, past returns, and conditional skewness in stock prices," Journal of Financial Economics, Elsevier, vol. 61(3), pages 345-381, September.
    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. De Long, J Bradford & Andrei Shleifer & Lawrence H. Summers & Robert J. Waldmann, 1990. "Noise Trader Risk in Financial Markets," Journal of Political Economy, University of Chicago Press, vol. 98(4), pages 703-738, August.
    7. Shleifer, Andrei, 2000. "Inefficient Markets: An Introduction to Behavioral Finance," OUP Catalogue, Oxford University Press, number 9780198292272.
    8. 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..
    9. 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.
    10. 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.
    11. Alok Kumar, 2009. "Who Gambles in the Stock Market?," Journal of Finance, American Finance Association, vol. 64(4), pages 1889-1933, August.
    12. Mitchell A. Petersen, 2009. "Estimating Standard Errors in Finance Panel Data Sets: Comparing Approaches," The Review of Financial Studies, Society for Financial Studies, vol. 22(1), pages 435-480, January.
    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. William F. Sharpe, 1964. "Capital Asset Prices: A Theory Of Market Equilibrium Under Conditions Of Risk," Journal of Finance, American Finance Association, vol. 19(3), pages 425-442, September.
    15. Sensoy, Berk A., 2009. "Performance evaluation and self-designated benchmark indexes in the mutual fund industry," Journal of Financial Economics, Elsevier, vol. 92(1), pages 25-39, April.
    Full references (including those not matched with items on IDEAS)

    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, October.
    2. Andreas Oehler & Julian Schneider, 2022. "Gambling with lottery stocks?," Journal of Asset Management, Palgrave Macmillan, vol. 23(6), pages 477-503, October.
    3. Chabi-Yo, Fousseni & Ruenzi, Stefan & Weigert, Florian, 2018. "Crash Sensitivity and the Cross Section of Expected Stock Returns," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 53(3), pages 1059-1100, June.
    4. Alankar, Ashwin & Blausten, Peter & Scholes, Myron S., 2013. "The Cost of Constraints: Risk Management, Agency Theory and Asset Prices," Research Papers 2135, Stanford University, Graduate School of Business.
    5. Benjamin M Blau & Ryan J Whitby, 2017. "Range-based volatility, expected stock returns, and the low volatility anomaly," PLOS ONE, Public Library of Science, vol. 12(11), pages 1-19, November.
    6. Paul Schneider & Christian Wagner & Josef Zechner, 2020. "Low‐Risk Anomalies?," Journal of Finance, American Finance Association, vol. 75(5), pages 2673-2718, October.
    7. Jang, Jeewon & Kang, Jangkoo, 2019. "Probability of price crashes, rational speculative bubbles, and the cross-section of stock returns," Journal of Financial Economics, Elsevier, vol. 132(1), pages 222-247.
    8. Ohk, Seungbin & Ju, Biung-Ghi, 2021. "Capitalizing on prospect theory value: The Asian developed stock markets," Japan and the World Economy, Elsevier, vol. 57(C).
    9. Tariq Aziz & Valeed Ahmad Ansari, 2017. "Idiosyncratic volatility and stock returns: Indian evidence," Cogent Economics & Finance, Taylor & Francis Journals, vol. 5(1), pages 1420998-142, January.
    10. 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.
    11. Joshua Traut, 2023. "What we know about the low-risk anomaly: a literature review," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 37(3), pages 297-324, September.
    12. Zhong, Angel, 2018. "Idiosyncratic volatility in the Australian equity market," Pacific-Basin Finance Journal, Elsevier, vol. 50(C), pages 105-125.
    13. Zhu, Zhaobo & Ding, Wenjie & Jin, Yi & Shen, Dehua, 2023. "Dissecting the idiosyncratic volatility puzzle: A fundamental analysis approach," Research in International Business and Finance, Elsevier, vol. 66(C).
    14. Alshammari, Saad & Goto, Shingo, 2022. "Are lottery-like stocks overvalued in markets that have no lotteries?–Evidence from Saudi Arabia," Finance Research Letters, Elsevier, vol. 46(PB).
    15. Baars, Maren & Mohrschladt, Hannes, 2021. "An alternative behavioral explanation for the MAX effect," Journal of Economic Behavior & Organization, Elsevier, vol. 191(C), pages 868-886.
    16. Wang, Huijun & Yan, Jinghua & Yu, Jianfeng, 2017. "Reference-dependent preferences and the risk–return trade-off," Journal of Financial Economics, Elsevier, vol. 123(2), pages 395-414.
    17. Liu, Bibo & Wang, Huijun & Yu, Jianfeng & Zhao, Shen, 2020. "Time-varying demand for lottery: Speculation ahead of earnings announcements," Journal of Financial Economics, Elsevier, vol. 138(3), pages 789-817.
    18. Son, Nguyen Truong & Nguyen, Nhat Minh, 2019. "Prospect theory value and idiosyncratic volatility: Evidence from the Korean stock market," Journal of Behavioral and Experimental Finance, Elsevier, vol. 21(C), pages 113-122.
    19. 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.
    20. Shi, Huai-Long & Zhou, Wei-Xing, 2021. "Horse race of weekly idiosyncratic momentum strategies with respect to various risk metrics: Evidence from the Chinese stock market," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).

    More about this item

    Keywords

    volatility; anomaly; behavioral bias; institutional investor; individual investor;
    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:mof:journl:ppr022a. 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: Policy Research Institute (email available below). General contact details of provider: https://edirc.repec.org/data/prigvjp.html .

    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.