IDEAS home Printed from https://ideas.repec.org/a/eee/ecofin/v39y2017icp145-157.html
   My bibliography  Save this article

The impact of numerical superstition on the final digit of stock price

Author

Listed:
  • Ke, Wen-Chyan
  • Chen, Hueiling
  • Lin, Hsiou-Wei W.
  • Liu, Yo-Chia

Abstract

This paper investigates the extent to which the frequency distribution of the rightmost digit of stock prices is influenced by numerical superstitions. To identify the moderating variables that strengthen the superstition for numbers, we take into account factors including the amount of information, change of tick size, Chinese festivals, and bear market effect. Furthermore, we examine whether the frequency of lucky (unlucky) numbers as the final digit of prices decreases (increases) for firms with higher trading by institutional investors. The results indicate that investors in the Taiwan Stock Exchange tend to avoid number 4. Our results also find that the effects of numerical superstitions on the frequency of the final digit decrease when the amount of information increases. Investors appear to be more likely to avoid unlucky number 4 in the following four conditions: when the tick size becomes smaller, when it is one week before Chinese New Year, when it is the seventh month in the lunar calendar, and when it is in a bear market. We further document that institutional investors are not affected by numerical superstition. Moreover, our results support the notion that informed traders buy and sell more (less) actively the stocks with a lower (higher) frequency of prices ending with 4.

Suggested Citation

  • Ke, Wen-Chyan & Chen, Hueiling & Lin, Hsiou-Wei W. & Liu, Yo-Chia, 2017. "The impact of numerical superstition on the final digit of stock price," The North American Journal of Economics and Finance, Elsevier, vol. 39(C), pages 145-157.
  • Handle: RePEc:eee:ecofin:v:39:y:2017:i:c:p:145-157
    DOI: 10.1016/j.najef.2016.10.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1062940816301218
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.najef.2016.10.003?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. David Easley & Soeren Hvidkjaer & Maureen O'Hara, 2002. "Is Information Risk a Determinant of Asset Returns?," Journal of Finance, American Finance Association, vol. 57(5), pages 2185-2221, October.
    2. Aitken, Michael & Brown, Philip & Buckland, Christine & Izan, H. Y. & Walter, Terry, 1996. "Price clustering on the Australian Stock Exchange," Pacific-Basin Finance Journal, Elsevier, vol. 4(2-3), pages 297-314, July.
    3. 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.
    4. Nicole M. Fortin & Andrew J. Hill & Jeff Huang, 2014. "Superstition In The Housing Market," Economic Inquiry, Western Economic Association International, vol. 52(3), pages 974-993, July.
    5. Shum, Matthew & Sun, Wei & Ye, Guangliang, 2014. "Superstition and “lucky” apartments: Evidence from transaction-level data," Journal of Comparative Economics, Elsevier, vol. 42(1), pages 109-117.
    6. 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.
    7. Clifford A. Ball & Walter N. Torous & Adrian E. Tschoegl, 1985. "The degree of price resolution: The case of the gold market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 5(1), pages 29-43, March.
    8. Michael J. Cooper & Roberto C. Gutierrez & Allaudeen Hameed, 2004. "Market States and Momentum," Journal of Finance, American Finance Association, vol. 59(3), pages 1345-1365, June.
    9. Harris, Lawrence, 1991. "Stock Price Clustering and Discreteness," The Review of Financial Studies, Society for Financial Studies, vol. 4(3), pages 389-415.
    10. Brown, Philip & Chua, Angeline & Mitchell, Jason, 2002. "The influence of cultural factors on price clustering: Evidence from Asia-Pacific stock markets," Pacific-Basin Finance Journal, Elsevier, vol. 10(3), pages 307-332, June.
    11. David Hirshleifer & Ming Jian & Huai Zhang, 2018. "Superstition and Financial Decision Making," Management Science, INFORMS, vol. 64(1), pages 235-252, January.
    12. Charles Cao & Oliver Hansch & Xiaoxin Wang, 2009. "The information content of an open limit‐order book," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 29(1), pages 16-41, January.
    13. Brown, Philip & Mitchell, Jason, 2008. "Culture and stock price clustering: Evidence from The Peoples' Republic of China," Pacific-Basin Finance Journal, Elsevier, vol. 16(1-2), pages 95-120, January.
    14. William Lin, Hsiou-Wei & Ke, Wen-Chyan, 2011. "A computing bias in estimating the probability of informed trading," Journal of Financial Markets, Elsevier, vol. 14(4), pages 625-640, November.
    15. Frank Fehle, 2004. "Bid-Ask Spreads and Institutional Ownership," Review of Quantitative Finance and Accounting, Springer, vol. 22(4), pages 275-292, June.
    16. Ahn, Hee-Joon & Cai, Jun & Cheung, Yan Leung, 2005. "Price clustering on the limit-order book: Evidence from the Stock Exchange of Hong Kong," Journal of Financial Markets, Elsevier, vol. 8(4), pages 421-451, November.
    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. Tao Chen & Andreas Karathanasopoulos & Stanley Iat-Meng Ko & Chia Chun Lo, 2020. "Lucky lots and unlucky investors," Review of Quantitative Finance and Accounting, Springer, vol. 54(2), pages 735-751, February.

    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. Bai, Min & Xu, Limin & Yu, Chia-Feng (Jeffrey) & Zurbruegg, Ralf, 2020. "Superstition and stock price crash risk," Pacific-Basin Finance Journal, Elsevier, vol. 60(C).
    2. repec:cup:judgdm:v:11:y:2016:i:3:p:243-259 is not listed on IDEAS
    3. Tong V. Wang & Rogier J. D. Potter van Loon & Martijn J. van den Assem & Dennie van Dolder, 2016. "Number preferences in lotteries," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 11(3), pages 243-259, May.
    4. Narayan, Paresh Kumar & Smyth, Russell, 2013. "Has political instability contributed to price clustering on Fiji's stock market?," Journal of Asian Economics, Elsevier, vol. 28(C), pages 125-130.
    5. Vladim'ir Hol'y & Petra Tomanov'a, 2021. "Modeling Price Clustering in High-Frequency Prices," Papers 2102.12112, arXiv.org, revised Mar 2021.
    6. Kwong Wing Chau & Danika Wright & Ervi Liusman, 2018. "The cost of a lucky price," ERES eres2018_240, European Real Estate Society (ERES).
    7. Narayan, Paresh Kumar & Narayan, Seema & Popp, Stephan & D'Rosario, Michael, 2011. "Share price clustering in Mexico," International Review of Financial Analysis, Elsevier, vol. 20(2), pages 113-119, April.
    8. Baig, Ahmed S. & Sabah, Nasim, 2020. "Does short selling affect the clustering of stock prices?," The Quarterly Review of Economics and Finance, Elsevier, vol. 76(C), pages 270-277.
    9. Utpal Bhattacharya & Wei-Yu Kuo & Tse-Chun Lin & Jing Zhao, 2018. "Do Superstitious Traders Lose Money?," Management Science, INFORMS, vol. 64(8), pages 3772-3791, August.
    10. Bill M. Cai & Charlie X. Cai & Kevin Keasey, 2007. "Influence of cultural factors on price clustering and price resistance in China's stock markets," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 47(4), pages 623-641, December.
    11. Robert Brooks & Edwyna Harris & Yovina Joymungul, 2013. "Price clustering in Australian water markets," Applied Economics, Taylor & Francis Journals, vol. 45(6), pages 677-685, February.
    12. Meng, Lei & Verousis, Thanos & ap Gwilym, Owain, 2013. "A substitution effect between price clustering and size clustering in credit default swaps," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 24(C), pages 139-152.
    13. Mazza, Paolo, 2015. "Price dynamics and market liquidity: An intraday event study on Euronext," The Quarterly Review of Economics and Finance, Elsevier, vol. 56(C), pages 139-153.
    14. Li, Xin & Li, Shenghong & Xu, Chong, 2020. "Price clustering in Bitcoin market—An extension," Finance Research Letters, Elsevier, vol. 32(C).
    15. Roger, Patrick & D’Hondt, Catherine & Plotkina, Daria & Hoffmann, Arvid, 2022. "Number 19: Another Victim of the COVID‐19 Pandemic?," LIDAM Discussion Papers LFIN 2022007, Université catholique de Louvain, Louvain Finance (LFIN).
    16. Ahmed S. Baig & Benjamin M. Blau & R. Jared DeLisle, 2022. "Does mutual fund ownership reduce stock price clustering? Evidence from active and index funds," Review of Quantitative Finance and Accounting, Springer, vol. 58(2), pages 615-647, February.
    17. Das, Sougata & Kadapakkam, Palani-Rajan, 2020. "Machine over Mind? Stock price clustering in the era of algorithmic trading," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    18. Cenesizoglu, Tolga & Grass, Gunnar, 2018. "Bid- and ask-side liquidity in the NYSE limit order book," Journal of Financial Markets, Elsevier, vol. 38(C), pages 14-38.
    19. Owain ap Gwilym & Evamena Alibo, 2003. "Decreased price clustering in FTSE100 futures contracts following a transfer from floor to electronic trading," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 23(7), pages 647-659, July.
    20. Narayan, Paresh Kumar, 2022. "Evidence of oil market price clustering during the COVID-19 pandemic," International Review of Financial Analysis, Elsevier, vol. 80(C).
    21. Donglian Ma & Hisashi Tanizaki, 2022. "Intraday patterns of price clustering in Bitcoin," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-25, December.

    More about this item

    Keywords

    Numerical superstition; Lucky number; Unlucky number; Bear market effect; Institutional investor trading;
    All these keywords.

    JEL classification:

    • G02 - Financial Economics - - General - - - Behavioral Finance: Underlying Principles
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors

    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:ecofin:v:39:y:2017:i:c:p:145-157. 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/620163 .

    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.