IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v26y2018icp40-46.html
   My bibliography  Save this article

Predictive ability of low-frequency volatility measures: Evidence from the Hong Kong stock markets

Author

Listed:
  • Gan, Christopher
  • Nartea, Gilbert V.
  • Wu, Ji (George)

Abstract

We employ low-frequency data to estimate historical volatility measures for Hong Kong stocks and examine the relationship between these measures and the one-month ahead stock return over thirty-five years. First, we employ a stock's past three-year weekly return to compute idiosyncratic volatility. Second, we use a stock's past three-year maximum weekly return to create a MAX measure. We find that both IVOL and MAX are significant and negatively related to the one-month ahead stock return. Both effects co-exist in the Hong Kong stock markets and are robust after controlling for the financial crisis, January effect, and tiny stocks.

Suggested Citation

  • Gan, Christopher & Nartea, Gilbert V. & Wu, Ji (George), 2018. "Predictive ability of low-frequency volatility measures: Evidence from the Hong Kong stock markets," Finance Research Letters, Elsevier, vol. 26(C), pages 40-46.
    • Handle: RePEc:eee:finlet:v:26:y:2018:i:c:p:40-46
    DOI: 10.1016/j.frl.2017.11.007
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S154461231730346X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.frl.2017.11.007?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. 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.
    2. Khovansky, Serguey & Zhylyevskyy, Oleksandr, 2013. "Impact of idiosyncratic volatility on stock returns: A cross-sectional study," Journal of Banking & Finance, Elsevier, vol. 37(8), pages 3064-3075.
    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. 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.
    5. Bekaert, Geert & Hodrick, Robert J. & Zhang, Xiaoyan, 2012. "Aggregate Idiosyncratic Volatility," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 47(6), pages 1155-1185, December.
    6. Bali, Turan G. & Cakici, Nusret, 2008. "Idiosyncratic Volatility and the Cross Section of Expected Returns," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 43(1), pages 29-58, March.
    7. James S. Doran & Danling Jiang & David R. Peterson, 2011. "Gambling Preference and the New Year Effect of Assets with Lottery Features," Review of Finance, European Finance Association, vol. 16(3), pages 685-731.
    8. Chan, Yue-Cheong & Chui, Andy C.W., 2016. "Gambling in the Hong Kong stock market," International Review of Economics & Finance, Elsevier, vol. 44(C), pages 204-218.
    9. Nartea, Gilbert V. & Wu, Ji, 2013. "Is there a volatility effect in the Hong Kong stock market?," Pacific-Basin Finance Journal, Elsevier, vol. 25(C), pages 119-135.
    10. Eric C. Chang & Joseph W. Cheng & Yinghui Yu, 2007. "Short‐Sales Constraints and Price Discovery: Evidence from the Hong Kong Market," Journal of Finance, American Finance Association, vol. 62(5), pages 2097-2121, October.
    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. Angelidis, Timotheos & Tessaromatis, Nikolaos, 2008. "Idiosyncratic volatility and equity returns: UK evidence," International Review of Financial Analysis, Elsevier, vol. 17(3), pages 539-556, June.
    13. 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.
    14. Ozgur S. Ince & R. Burt Porter, 2006. "Individual Equity Return Data From Thomson Datastream: Handle With Care!," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 29(4), pages 463-479, December.
    15. 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.
    16. Blitz, D.C. & van Vliet, P., 2007. "The Volatility Effect: Lower Risk without Lower Return," ERIM Report Series Research in Management ERS-2007-044-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    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. 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.
    2. 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.
    3. 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.
    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. Adam Zaremba & Jacob Koby Shemer, 2018. "Price-Based Investment Strategies," Springer Books, Springer, number 978-3-319-91530-2, November.
    6. Nartea, Gilbert V. & Wu, Ji, 2013. "Is there a volatility effect in the Hong Kong stock market?," Pacific-Basin Finance Journal, Elsevier, vol. 25(C), pages 119-135.
    7. Su, Zhi & Shu, Tengjia & Yin, Libo, 2018. "The pricing effect of the common pattern in firm-level idiosyncratic volatility: Evidence from A-Share stocks of China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 497(C), pages 218-235.
    8. Cotter, John & Sullivan, Niall O' & Rossi, Francesco, 2015. "The conditional pricing of systematic and idiosyncratic risk in the UK equity market," International Review of Financial Analysis, Elsevier, vol. 37(C), pages 184-193.
    9. Ali, Syed Riaz Mahmood & Hasan, Mohammad Nurul & Östermark, Ralf, 2020. "Are idiosyncratic risk and extreme positive return priced in the Indian equity market?," International Review of Economics & Finance, Elsevier, vol. 70(C), pages 530-545.
    10. 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.
    11. Hsin, Chin-Wen & Peng, Shu-Cing, 2023. "Investor propensity to speculate and price delay in emerging markets," International Review of Financial Analysis, Elsevier, vol. 86(C).
    12. Nam, Kiseok & Khaksari, Shahriar & Kang, Moonsoo, 2017. "Trend in aggregate idiosyncratic volatility," Review of Financial Economics, Elsevier, vol. 35(C), pages 11-28.
    13. 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).
    14. Annaert, Jan & De Ceuster, Marc & Van Doninck, Freek, 2022. "Decomposing the idiosyncratic volatility anomaly among euro area stocks," Finance Research Letters, Elsevier, vol. 47(PB).
    15. Andreas Oehler & Julian Schneider, 2022. "Gambling with lottery stocks?," Journal of Asset Management, Palgrave Macmillan, vol. 23(6), pages 477-503, October.
    16. Zhong, Angel, 2018. "Idiosyncratic volatility in the Australian equity market," Pacific-Basin Finance Journal, Elsevier, vol. 50(C), pages 105-125.
    17. Cao, Jie & Han, Bing, 2016. "Idiosyncratic risk, costly arbitrage, and the cross-section of stock returns," Journal of Banking & Finance, Elsevier, vol. 73(C), pages 1-15.
    18. Gao, Ya & Han, Xing & Xiong, Xiong, 2021. "Loss from the chasing of MAX stocks: Evidence from China," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    19. 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.
    20. 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.

    More about this item

    Keywords

    Total volatility; Idiosyncratic volatility; Maximum weekly returns; Asset pricing; Weekly data; Hong Kong stock markets;
    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

    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:finlet:v:26:y:2018:i:c:p:40-46. 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/frl .

    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.