IDEAS home Printed from https://ideas.repec.org/a/eee/pacfin/v61y2020ics0927538x19305815.html
   My bibliography  Save this article

Distraction effects on stock return co-movements: Confirmation from the Shenzhen and Shanghai stock markets

Author

Listed:
  • Zhaunerchyk, Katsiaryna
  • Haghighi, Afshin
  • Oliver, Barry

Abstract

This study replicates a key part of the paper by Huang et al. (2019) using the original framework and examines the findings in an alternative stock market. Huang et al. (2019) document that, on days with attention shocks driven by major jackpot lottery drawings, stock return co-movement increases in the Taiwan stock market. They suggest that in distraction events, due to limited cognitive capacity to allocate attention, inventors shift their focus of attention from firm-specific information to broader market-specific information. This leads to higher stock return co-movement. Our study aims to test the reproducibility of the empirical framework presented by Huang et al. (2019) and the robustness of the reported results in the Shenzhen and Shanghai stock markets. The results confirm the original paper's finding of increased stock return co-movement on high distraction days and provide similar results in the Shenzhen and Shanghai stock markets (together as well as separately).

Suggested Citation

  • Zhaunerchyk, Katsiaryna & Haghighi, Afshin & Oliver, Barry, 2020. "Distraction effects on stock return co-movements: Confirmation from the Shenzhen and Shanghai stock markets," Pacific-Basin Finance Journal, Elsevier, vol. 61(C).
    • Handle: RePEc:eee:pacfin:v:61:y:2020:i:c:s0927538x19305815
    DOI: 10.1016/j.pacfin.2020.101301
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0927538X19305815
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.pacfin.2020.101301?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. Peng, Lin & Xiong, Wei, 2006. "Investor attention, overconfidence and category learning," Journal of Financial Economics, Elsevier, vol. 80(3), pages 563-602, June.
    2. Veldkamp, Laura & Wolfers, Justin, 2007. "Aggregate shocks or aggregate information? Costly information and business cycle comovement," Journal of Monetary Economics, Elsevier, vol. 54(Supplemen), pages 37-55, September.
    3. Laura L. Veldkamp, 2006. "Information Markets and the Comovement of Asset Prices," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 73(3), pages 823-845.
    4. Thomas J. Chemmanur & An Yan, 2019. "Advertising, Attention, and Stock Returns," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 9(03), pages 1-51, September.
    5. repec:bla:jfinan:v:59:y:2004:i:1:p:65-105 is not listed on IDEAS
    6. Huang, Shiyang & Huang, Yulin & Lin, Tse-Chun, 2019. "Attention allocation and return co-movement: Evidence from repeated natural experiments," Journal of Financial Economics, Elsevier, vol. 132(2), pages 369-383.
    7. Choi, Sujung & Choi, Woon Youl, 2019. "Effects of limited attention on investors' trading behavior: Evidence from online ranking data," Pacific-Basin Finance Journal, Elsevier, vol. 56(C), pages 273-289.
    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. Corbet, Shaen & Goodell, John W., 2022. "The reputational contagion effects of ransomware attacks," Finance Research Letters, Elsevier, vol. 47(PB).
    2. Kou, Shubo & Ma, Xiyuan, 2024. "From Gambling to Gaming: The Crowding Out Effect," Finance Research Letters, Elsevier, vol. 59(C).
    3. Li, Yue & Goodell, John W. & Shen, Dehua, 2021. "Comparing search-engine and social-media attentions in finance research: Evidence from cryptocurrencies," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 723-746.
    4. Hu, Yitong & Li, Xiao & Goodell, John W. & Shen, Dehua, 2021. "Investor attention shocks and stock co-movement: Substitution or reinforcement?," International Review of Financial Analysis, Elsevier, vol. 73(C).
    5. Su, Fei & Wang, Xinyi, 2021. "Investor co-attention and stock return co-movement: Evidence from China’s A-share stock market," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).

    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. Hu, Yitong & Shen, Dehua & Urquhart, Andrew, 2023. "Attention allocation and cryptocurrency return co-movement: Evidence from the stock market," International Review of Economics & Finance, Elsevier, vol. 88(C), pages 1173-1185.
    2. Prange, Philipp, 2021. "Does online investor attention drive the co-movement of stock-, commodity-, and energy markets? Insights from Google searches," Energy Economics, Elsevier, vol. 99(C).
    3. Do, Hung X. & Nguyen, Nhut H. & Nguyen, Quan M.P. & Truong, Cameron, 2023. "Aerospace competition, investor attention, and stock return comovement," Journal of Economic Behavior & Organization, Elsevier, vol. 215(C), pages 40-59.
    4. Ehrmann, Michael & Jansen, David-Jan, 2022. "Stock return comovement when investors are distracted: More, and more homogeneous," Journal of International Money and Finance, Elsevier, vol. 129(C).
    5. Gondhi, Naveen, 2023. "Rational inattention, misallocation, and the aggregate economy," Journal of Monetary Economics, Elsevier, vol. 136(C), pages 50-75.
    6. Chen, Zilin & Guo, Li & Tu, Jun, 2021. "Media connection and return comovement," Journal of Economic Dynamics and Control, Elsevier, vol. 130(C).
    7. Lu, Shan & Zhao, Jichang, 2024. "Investor network and stock return comovement: Information-seeking through intragroup and intergroup followings," International Review of Financial Analysis, Elsevier, vol. 93(C).
    8. Huang, Shiyang & Huang, Yulin & Lin, Tse-Chun, 2019. "Attention allocation and return co-movement: Evidence from repeated natural experiments," Journal of Financial Economics, Elsevier, vol. 132(2), pages 369-383.
    9. Ma, Rui & Marshall, Ben R. & Nguyen, Hung T. & Nguyen, Nhut H. & Visaltanachoti, Nuttawat, 2022. "Climate events and return comovement," Journal of Financial Markets, Elsevier, vol. 61(C).
    10. Seyed Mohammadreza Davoodalhosseini, 2020. "Adverse Selection With Heterogeneously Informed Agents," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 61(3), pages 1307-1358, August.
    11. Charles Ka Yui Leung & Patrick Wai Yin Cheung & Edward Chi Ho Tang, 2013. "Financial Crisis and the Co-movements of Housing Sub-markets: Do relationships change after a crisis?," International Real Estate Review, Global Social Science Institute, vol. 16(1), pages 68-118.
    12. Premal P Vora, 2020. "Clogged information flow and stock-market sluggishness," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-13, July.
    13. Jiao, Yawen, 2024. "Managing decision fatigue: Evidence from analysts’ earnings forecasts," Journal of Accounting and Economics, Elsevier, vol. 77(1).
    14. Cheema, Arbab K. & Eshraghi, Arman & Wang, Qingwei, 2023. "Macroeconomic news and price synchronicity," Journal of Empirical Finance, Elsevier, vol. 73(C), pages 390-412.
    15. Qian Chen & Xiang Gao & Jianming Mo & Zhouling Xu, 2022. "Market Reaction to Local Attention around Earnings Announcements in China: Evidence from Internet Search Activity," IJFS, MDPI, vol. 10(4), pages 1-26, October.
    16. Dew-Becker, Ian & Nathanson, Charles G., 2019. "Directed attention and nonparametric learning," Journal of Economic Theory, Elsevier, vol. 181(C), pages 461-496.
    17. Zheng, Zunxin & Qiu, Zhongjie & Li, Mengjia & Ding, Wenjie, 2024. "High-speed rail and stock return comovement in China," Research in International Business and Finance, Elsevier, vol. 67(PA).
    18. Chang, Young Bong & Kwon, YoungOk, 2018. "Ambiguities in valuing information technology firms: Do internet searches help?," Journal of Business Research, Elsevier, vol. 92(C), pages 260-269.
    19. Yuan, Ying & Fan, Xiaoqian & Li, Yiou, 2022. "Do local and non-local retail investor attention impact stock returns differently?," Pacific-Basin Finance Journal, Elsevier, vol. 74(C).
    20. Chen, Zhongdong & Craig, Karen Ann, 2023. "Active attention, retail investor base, and stock returns," Journal of Behavioral and Experimental Finance, Elsevier, vol. 39(C).

    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:pacfin:v:61:y:2020:i:c:s0927538x19305815. 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/pacfin .

    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.