IDEAS home Printed from https://ideas.repec.org/a/eee/finana/v81y2022ics1057521920302702.html
   My bibliography  Save this article

Retail investor attention and the limit order book: Intraday analysis of attention-based trading

Author

Listed:
  • Meshcheryakov, Artem
  • Winters, Drew B.

Abstract

We are the first to examine how intraday changes in retail investor attention, measured by hourly Google searches, affect trading activity and informativeness of trades. High levels of Google search activity are followed in the next hour by more intensive trading in all stocks. The increased trading activity is initiated by retail investors as evidenced by the reduced size of new orders. After googling a company, retail investors do not become informed in the traditional sense; rather, they act as noise traders, who mistake noise for information, as their orders are picked off by truly informed traders.

Suggested Citation

  • Meshcheryakov, Artem & Winters, Drew B., 2022. "Retail investor attention and the limit order book: Intraday analysis of attention-based trading," International Review of Financial Analysis, Elsevier, vol. 81(C).
    • Handle: RePEc:eee:finana:v:81:y:2022:i:c:s1057521920302702
    DOI: 10.1016/j.irfa.2020.101627
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1057521920302702
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.irfa.2020.101627?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. Sander van Veldhuizen & Benedikt Vogt & Bart Voogt, 2016. "Internet searches and transactions on the Dutch housing market," Applied Economics Letters, Taylor & Francis Journals, vol. 23(18), pages 1321-1324, December.
    2. Shleifer, Andrei & Summers, Lawrence H, 1990. "The Noise Trader Approach to Finance," Journal of Economic Perspectives, American Economic Association, vol. 4(2), pages 19-33, Spring.
    3. Ron Kaniel & Gideon Saar & Sheridan Titman, 2008. "Individual Investor Trading and Stock Returns," Journal of Finance, American Finance Association, vol. 63(1), pages 273-310, February.
    4. Fantazzini, Dean & Toktamysova, Zhamal, 2015. "Forecasting German car sales using Google data and multivariate models," International Journal of Production Economics, Elsevier, vol. 170(PA), pages 97-135.
    5. Nikolaos Askitas & Klaus F. Zimmermann, 2009. "Google Econometrics and Unemployment Forecasting," Applied Economics Quarterly (formerly: Konjunkturpolitik), Duncker & Humblot, Berlin, vol. 55(2), pages 107-120.
    6. Sander van Veldhuizen & Benedikt Vogt & Bart Voogt, 2016. "Internet searches and transactions on the housing market," CPB Discussion Paper 325.rdf, CPB Netherlands Bureau for Economic Policy Analysis.
    7. Sander van Veldhuizen & Benedikt Vogt & Bart Voogt, 2016. "Internet searches and transactions on the housing market," CPB Discussion Paper 325, CPB Netherlands Bureau for Economic Policy Analysis.
    8. Glosten, Lawrence R. & Milgrom, Paul R., 1985. "Bid, ask and transaction prices in a specialist market with heterogeneously informed traders," Journal of Financial Economics, Elsevier, vol. 14(1), pages 71-100, March.
    9. Glosten, Lawrence R, 1994. "Is the Electronic Open Limit Order Book Inevitable?," Journal of Finance, American Finance Association, vol. 49(4), pages 1127-1161, September.
    10. Merton, Robert C, 1987. "A Simple Model of Capital Market Equilibrium with Incomplete Information," Journal of Finance, American Finance Association, vol. 42(3), pages 483-510, July.
    11. Thomas Dimpfl & Stephan Jank, 2016. "Can Internet Search Queries Help to Predict Stock Market Volatility?," European Financial Management, European Financial Management Association, vol. 22(2), pages 171-192, March.
    12. Matthias Bank & Martin Larch & Georg Peter, 2011. "Google search volume and its influence on liquidity and returns of German stocks," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 25(3), pages 239-264, September.
    13. Azi Ben-Rephael & Zhi Da & Ryan D. Israelsen, 2017. "It Depends on Where You Search: Institutional Investor Attention and Underreaction to News," The Review of Financial Studies, Society for Financial Studies, vol. 30(9), pages 3009-3047.
    14. Lily Fang & Joel Peress, 2009. "Media Coverage and the Cross‐section of Stock Returns," Journal of Finance, American Finance Association, vol. 64(5), pages 2023-2052, October.
    15. Kyle, Albert S, 1985. "Continuous Auctions and Insider Trading," Econometrica, Econometric Society, vol. 53(6), pages 1315-1335, November.
    16. Joseph, Kissan & Babajide Wintoki, M. & Zhang, Zelin, 2011. "Forecasting abnormal stock returns and trading volume using investor sentiment: Evidence from online search," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1116-1127, October.
    17. Aouadi, Amal & Arouri, Mohamed & Teulon, Frédéric, 2013. "Investor attention and stock market activity: Evidence from France," Economic Modelling, Elsevier, vol. 35(C), pages 674-681.
    18. Zhi Da & Joseph Engelberg & Pengjie Gao, 2011. "In Search of Attention," Journal of Finance, American Finance Association, vol. 66(5), pages 1461-1499, October.
    19. Hyunyoung Choi & Hal Varian, 2012. "Predicting the Present with Google Trends," The Economic Record, The Economic Society of Australia, vol. 88(s1), pages 2-9, June.
    20. Juhani T. Linnainmaa, 2010. "Do Limit Orders Alter Inferences about Investor Performance and Behavior?," Journal of Finance, American Finance Association, vol. 65(4), pages 1473-1506, August.
    21. Michael S. Drake & Darren T. Roulstone & Jacob R. Thornock, 2012. "Investor Information Demand: Evidence from Google Searches Around Earnings Announcements," Journal of Accounting Research, Wiley Blackwell, vol. 50(4), pages 1001-1040, September.
    22. Brad M. Barber & Terrance Odean, 2008. "All That Glitters: The Effect of Attention and News on the Buying Behavior of Individual and Institutional Investors," The Review of Financial Studies, Society for Financial Studies, vol. 21(2), pages 785-818, April.
    23. Jeremy Ginsberg & Matthew H. Mohebbi & Rajan S. Patel & Lynnette Brammer & Mark S. Smolinski & Larry Brilliant, 2009. "Detecting influenza epidemics using search engine query data," Nature, Nature, vol. 457(7232), pages 1012-1014, February.
    24. Robert Bloomfield & Maureen O'Hara & Gideon Saar, 2009. "How Noise Trading Affects Markets: An Experimental Analysis," The Review of Financial Studies, Society for Financial Studies, vol. 22(6), pages 2275-2302, June.
    25. Alok Kumar & Charles M.C. Lee, 2006. "Retail Investor Sentiment and Return Comovements," Journal of Finance, American Finance Association, vol. 61(5), pages 2451-2486, October.
    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. David Ardia & Cl'ement Aymard & Tolga Cenesizoglu, 2023. "Fast and Furious: A High-Frequency Analysis of Robinhood Users' Trading Behavior," Papers 2307.11012, arXiv.org.
    2. Chen, Zhongdong & Craig, Karen Ann, 2023. "Active attention, retail investor base, and stock returns," Journal of Behavioral and Experimental Finance, Elsevier, vol. 39(C).
    3. Kuo, Wei-Yu & Zhao, Jing, 2023. "Pre-holiday limit order cancellation of individual and institutional investors," Finance Research Letters, Elsevier, vol. 52(C).
    4. Goodell, John W. & Kumar, Satish & Li, Xiao & Pattnaik, Debidutta & Sharma, Anuj, 2022. "Foundations and research clusters in investor attention: Evidence from bibliometric and topic modelling analysis," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 511-529.

    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. Chen, Zhongdong & Craig, Karen Ann, 2023. "Active attention, retail investor base, and stock returns," Journal of Behavioral and Experimental Finance, Elsevier, vol. 39(C).
    2. Aouadi, Amal & Arouri, Mohamed & Roubaud, David, 2018. "Information demand and stock market liquidity: International evidence," Economic Modelling, Elsevier, vol. 70(C), pages 194-202.
    3. Chaiyuth Padungsaksawasdi & Sirimon Treepongkaruna & Robert Brooks, 2019. "Investor Attention and Stock Market Activities: New Evidence from Panel Data," IJFS, MDPI, vol. 7(2), pages 1-19, June.
    4. Tariq Aziz & Valeed Ahmad Ansari, 2021. "How Does Google Search Affect the Stock Market? Evidence from Indian Companies," Vision, , vol. 25(2), pages 224-232, June.
    5. Adachi, Yuta & Masuda, Motoki & Takeda, Fumiko, 2017. "Google search intensity and its relationship to the returns and liquidity of Japanese startup stocks," Pacific-Basin Finance Journal, Elsevier, vol. 46(PB), pages 243-257.
    6. Nguyen, Cuong & Hoang, Lai & Shim, Jungwook & Truong, Phuong, 2020. "Internet search intensity, liquidity and returns in emerging markets," Research in International Business and Finance, Elsevier, vol. 52(C).
    7. Christophe Desagre & Catherine D'Hondt, 2020. "Googlization and retail investors' trading activity," LIDAM Discussion Papers LFIN 2020004, Université catholique de Louvain, Louvain Finance (LFIN).
    8. Goodell, John W. & Kumar, Satish & Li, Xiao & Pattnaik, Debidutta & Sharma, Anuj, 2022. "Foundations and research clusters in investor attention: Evidence from bibliometric and topic modelling analysis," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 511-529.
    9. Aouadi, Amal & Arouri, Mohamed & Teulon, Frédéric, 2013. "Investor attention and stock market activity: Evidence from France," Economic Modelling, Elsevier, vol. 35(C), pages 674-681.
    10. Desagre, Christophe & D’Hondt, Catherine, 2021. "Googlization and retail trading activity," Journal of Behavioral and Experimental Finance, Elsevier, vol. 29(C).
    11. Semen Son-Turan, 2016. "The Impact of Investor Sentiment on the "Leverage Effect"," International Econometric Review (IER), Econometric Research Association, vol. 8(1), pages 4-18, April.
    12. Melody Y. Huang & Randall R. Rojas & Patrick D. Convery, 2020. "Forecasting stock market movements using Google Trend searches," Empirical Economics, Springer, vol. 59(6), pages 2821-2839, December.
    13. Behrendt, Simon & Peter, Franziska J. & Zimmermann, David J., 2020. "An encyclopedia for stock markets? Wikipedia searches and stock returns," International Review of Financial Analysis, Elsevier, vol. 72(C).
    14. Geng, Yuedan & Ye, Qiang & Jin, Yu & Shi, Wen, 2022. "Crowd wisdom and internet searches: What happens when investors search for stocks?," International Review of Financial Analysis, Elsevier, vol. 82(C).
    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. repec:ipg:wpaper:2014-405 is not listed on IDEAS
    17. Smales, L.A., 2021. "Investor attention and global market returns during the COVID-19 crisis," International Review of Financial Analysis, Elsevier, vol. 73(C).
    18. Owain Ap Gwilym & Iftekhar Hasan & Qingwei Wang & Ru Xie, 2016. "In Search of Concepts: The Effects of Speculative Demand on Stock Returns," European Financial Management, European Financial Management Association, vol. 22(3), pages 427-449, June.
    19. Dong, Dayong & Wu, Keke & Fang, Jianchun & Gozgor, Giray & Yan, Cheng, 2022. "Investor attention factors and stock returns: Evidence from China," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 77(C).
    20. Blankespoor, Elizabeth & deHaan, Ed & Marinovic, Iván, 2020. "Disclosure processing costs, investors’ information choice, and equity market outcomes: A review," Journal of Accounting and Economics, Elsevier, vol. 70(2).
    21. Semen Son Turan, 2014. "Internet Search Volume and Stock Return Volatility: The Case of Turkish Companies," Information Management and Business Review, AMH International, vol. 6(6), pages 317-328.

    More about this item

    Keywords

    Retail; Investors; Attention; Limit order book; Trading; Internet; Searches; Google; Market microstructure;
    All these keywords.

    JEL classification:

    • 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:finana:v:81:y:2022:i:c:s1057521920302702. 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/620166 .

    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.