IDEAS home Printed from https://ideas.repec.org/a/eee/ecmode/v83y2019icp141-149.html
   My bibliography  Save this article

Noise traders and smart money: Evidence from online searches

Author

Listed:
  • Hervé, Fabrice
  • Zouaoui, Mohamed
  • Belvaux, Bertrand

Abstract

Traditional finance theory considers that the impact of noise traders' attention on asset prices is offset by attention from smart investors. This paper uses online search data to study the influence of noise traders and smart investors on stock returns and volatility. Adopting an original approach, we construct a proxy for smart investor attention based on investors' online search behavior provided by Wikipedia Page Traffic. We combine this new measure with a standard measure of noise traders' attention as proxied by Google Search Volume Index. We show for a sample of 87 French firms over the period 2008–2018 that only noise traders' attention influences stock returns. Noise traders' attention increases volatility by creating an extra risk that is priced into the market. Conversely, smart investors' attention decreases volatility because their presence stabilizes stock prices by reducing uncertainty. Our empirical results support a behavioral explanation of stock prices.

Suggested Citation

  • Hervé, Fabrice & Zouaoui, Mohamed & Belvaux, Bertrand, 2019. "Noise traders and smart money: Evidence from online searches," Economic Modelling, Elsevier, vol. 83(C), pages 141-149.
  • Handle: RePEc:eee:ecmode:v:83:y:2019:i:c:p:141-149
    DOI: 10.1016/j.econmod.2019.02.005
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0264999318308629
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.econmod.2019.02.005?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 look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Márton Mestyán & Taha Yasseri & János Kertész, 2013. "Early Prediction of Movie Box Office Success Based on Wikipedia Activity Big Data," PLOS ONE, Public Library of Science, vol. 8(8), pages 1-8, August.
    2. Terrance Odean., 1996. "Volume, Volatility, Price and Profit When All Trader Are Above Average," Research Program in Finance Working Papers RPF-266, University of California at Berkeley.
    3. 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.
    4. Eric Girard & Rita Biswas, 2007. "Trading Volume and Market Volatility: Developed versus Emerging Stock Markets," The Financial Review, Eastern Finance Association, vol. 42(3), pages 429-459, August.
    5. Thierry Foucault & David Sraer & David J. Thesmar, 2011. "Individual Investors and Volatility," Journal of Finance, American Finance Association, vol. 66(4), pages 1369-1406, August.
    6. Amir Rubin & Eran Rubin, 2010. "Informed Investors and the Internet," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 37(7‐8), pages 841-865, July.
    7. Karpoff, Jonathan M., 1987. "The Relation between Price Changes and Trading Volume: A Survey," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 22(1), pages 109-126, March.
    8. Jeffrey L. Hoopes & Daniel H. Reck & Joel Slemrod, 2015. "Taxpayer Search for Information: Implications for Rational Attention," American Economic Journal: Economic Policy, American Economic Association, vol. 7(3), pages 177-208, August.
    9. Zhi Da & Joseph Engelberg & Pengjie Gao, 2011. "In Search of Attention," Journal of Finance, American Finance Association, vol. 66(5), pages 1461-1499, October.
    10. Hellwig, Martin F., 1980. "On the aggregation of information in competitive markets," Journal of Economic Theory, Elsevier, vol. 22(3), pages 477-498, June.
    11. Malcolm Baker & Jeffrey Wurgler, 2007. "Investor Sentiment in the Stock Market," Journal of Economic Perspectives, American Economic Association, vol. 21(2), pages 129-152, Spring.
    12. Li, Xin & Ma, Jian & Wang, Shouyang & Zhang, Xun, 2015. "How does Google search affect trader positions and crude oil prices?," Economic Modelling, Elsevier, vol. 49(C), pages 162-171.
    13. 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.
    14. Daniel, Kent, et al, 1997. "Measuring Mutual Fund Performance with Characteristic-Based Benchmarks," Journal of Finance, American Finance Association, vol. 52(3), pages 1035-1058, July.
    15. Daniel Andrei & Michael Hasler, 2015. "Investor Attention and Stock Market Volatility," Review of Financial Studies, Society for Financial Studies, vol. 28(1), pages 33-72.
    16. Bijl, Laurens & Kringhaug, Glenn & Molnár, Peter & Sandvik, Eirik, 2016. "Google searches and stock returns," International Review of Financial Analysis, Elsevier, vol. 45(C), pages 150-156.
    17. Robert J. Shiller, 2003. "From Efficient Markets Theory to Behavioral Finance," Journal of Economic Perspectives, American Economic Association, vol. 17(1), pages 83-104, Winter.
    18. Vozlyublennaia, Nadia, 2014. "Investor attention, index performance, and return predictability," Journal of Banking & Finance, Elsevier, vol. 41(C), pages 17-35.
    19. Brad M. Barber & Terrance Odean, 2008. "All That Glitters: The Effect of Attention and News on the Buying Behavior of Individual and Institutional Investors," Review of Financial Studies, Society for Financial Studies, vol. 21(2), pages 785-818, April.
    20. Bogan, Vicki, 2008. "Stock Market Participation and the Internet," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 43(1), pages 191-211, March.
    21. Giot, Pierre & Laurent, Sébastien & Petitjean, Mikael, 2010. "Trading activity, realized volatility and jumps," Journal of Empirical Finance, Elsevier, vol. 17(1), pages 168-175, January.
    22. Han, Liyan & Xu, Yang & Yin, Libo, 2018. "Does investor attention matter? The attention-return relationships in FX markets," Economic Modelling, Elsevier, vol. 68(C), pages 644-660.
    23. Herbert A. Simon, 1955. "A Behavioral Model of Rational Choice," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 69(1), pages 99-118.
    24. Harrison Hong & Jeremy C. Stein, 2007. "Disagreement and the Stock Market," Journal of Economic Perspectives, American Economic Association, vol. 21(2), pages 109-128, Spring.
    25. Amir Rubin & Eran Rubin, 2010. "Informed Investors and the Internet," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 37(7-8), pages 841-865.
    26. 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.
    27. Anwer S. Ahmed & Richard A. Schneible & Douglas E. Stevens, 2003. "An Empirical Analysis of the Effects of Online Trading on Stock Price and Trading Volume Reactions to Earnings Announcements," Contemporary Accounting Research, John Wiley & Sons, vol. 20(3), pages 413-439, September.
    28. Smith, Geoffrey Peter, 2012. "Google Internet search activity and volatility prediction in the market for foreign currency," Finance Research Letters, Elsevier, vol. 9(2), pages 103-110.
    29. Doron Avramov & Tarun Chordia & Amit Goyal, 2006. "The Impact of Trades on Daily Volatility," Review of Financial Studies, Society for Financial Studies, vol. 19(4), pages 1241-1277.
    30. Fabrice Hervé & Mohamed Zouaoui, 2014. "Quand la psychologie et la linguistique rencontrent la finance:le cas de la France," Revue Finance Contrôle Stratégie, revues.org, vol. 17(1), pages 25-46, March.
    31. 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.
    32. 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.
    33. Takeda, Fumiko & Wakao, Takumi, 2014. "Google search intensity and its relationship with returns and trading volume of Japanese stocks," Pacific-Basin Finance Journal, Elsevier, vol. 27(C), pages 1-18.
    34. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    35. Vlastakis, Nikolaos & Markellos, Raphael N., 2012. "Information demand and stock market volatility," Journal of Banking & Finance, Elsevier, vol. 36(6), pages 1808-1821.
    36. Wang, Jiang, 1994. "A Model of Competitive Stock Trading Volume," Journal of Political Economy, University of Chicago Press, vol. 102(1), pages 127-168, February.
    37. Fama, Eugene F & MacBeth, James D, 1973. "Risk, Return, and Equilibrium: Empirical Tests," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 607-636, May-June.
    38. Kyle, Albert S, 1985. "Continuous Auctions and Insider Trading," Econometrica, Econometric Society, vol. 53(6), pages 1315-1335, November.
    39. Chen, Gong-meng & Firth, Michael & Rui, Oliver M, 2001. "The Dynamic Relation between Stock Returns, Trading Volume, and Volatility," The Financial Review, Eastern Finance Association, vol. 36(3), pages 153-173, August.
    40. Terrance Odean, 1998. "Volume, Volatility, Price, and Profit When All Traders Are Above Average," Journal of Finance, American Finance Association, vol. 53(6), pages 1887-1934, December.
    41. Jim Giles, 2005. "Internet encyclopaedias go head to head," Nature, Nature, vol. 438(7070), pages 900-901, December.
    42. Michael Lemmon & Evgenia Portniaguina, 2006. "Consumer Confidence and Asset Prices: Some Empirical Evidence," Review of Financial Studies, Society for Financial Studies, vol. 19(4), pages 1499-1529.
    43. Gur Huberman & Tomer Regev, 2001. "Contagious Speculation and a Cure for Cancer: A Nonevent that Made Stock Prices Soar," Journal of Finance, American Finance Association, vol. 56(1), pages 387-396, February.
    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. Xun Zhang & Fengbin Lu & Rui Tao & Shouyang Wang, 2021. "The time-varying causal relationship between the Bitcoin market and internet attention," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-19, December.
    2. Chen, Xing & Diao, Xundi & Wu, Chongfeng, 2022. "Heterogeneous investor attention and post earnings announcement drift: Evidence from China," Economic Modelling, Elsevier, vol. 110(C).
    3. Thomas Boulton & Bill B. Francis & Thomas Shohfi & Daqi Xin, 2021. "Investor awareness or information asymmetry? Wikipedia and IPO underpricing," The Financial Review, Eastern Finance Association, vol. 56(3), pages 535-561, August.
    4. Chen, Xing & Wu, Chongfeng, 2022. "Retail investor attention and information asymmetry: Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 75(C).
    5. Wei Zhang & Kai Yan & Dehua Shen, 2021. "Can the Baidu Index predict realized volatility in the Chinese stock market?," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-31, December.
    6. Chen, Zhongdong & Craig, Karen Ann, 2023. "Active attention, retail investor base, and stock returns," Journal of Behavioral and Experimental Finance, Elsevier, vol. 39(C).
    7. Cheng, Feiyang & Chiao, Chaoshin & Wang, Chunfeng & Fang, Zhenming & Yao, Shouyu, 2021. "Does retail investor attention improve stock liquidity? A dynamic perspective," Economic Modelling, Elsevier, vol. 94(C), pages 170-183.

    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. Stéphane Goutte & David Guerreiro & Bilel Sanhaji & Sophie Saglio & Julien Chevallier, 2019. "International Financial Markets," Post-Print halshs-02183053, HAL.
    2. 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.
    3. Christophe Desagre & Catherine D'Hondt, 2020. "Googlization and retail investors' trading activity," LIDAM Discussion Papers LFIN 2020004, Université catholique de Louvain, Louvain Finance (LFIN).
    4. Takeda, Fumiko & Wakao, Takumi, 2014. "Google search intensity and its relationship with returns and trading volume of Japanese stocks," Pacific-Basin Finance Journal, Elsevier, vol. 27(C), pages 1-18.
    5. Gang Chu & John W. Goodell & Dehua Shen & Yongjie Zhang, 2022. "Machine learning to establish proxies for investor attention: evidence of improved stock-return prediction," Annals of Operations Research, Springer, vol. 318(1), pages 103-128, November.
    6. Agarwal, Shweta & Kumar, Shailendra & Goel, Utkarsh, 2019. "Stock market response to information diffusion through internet sources: A literature review," International Journal of Information Management, Elsevier, vol. 45(C), pages 118-131.
    7. Peltomäki, Jarkko & Graham, Michael & Hasselgren, Anton, 2018. "Investor attention to market categories and market volatility: The case of emerging markets," Research in International Business and Finance, Elsevier, vol. 44(C), pages 532-546.
    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 & Roubaud, David, 2018. "Information demand and stock market liquidity: International evidence," Economic Modelling, Elsevier, vol. 70(C), pages 194-202.
    10. Tihana Škrinjarić, 2019. "Time Varying Spillovers between the Online Search Volume and Stock Returns: Case of CESEE Markets," IJFS, MDPI, vol. 7(4), pages 1-30, October.
    11. Ramiah, Vikash & Xu, Xiaoming & Moosa, Imad A., 2015. "Neoclassical finance, behavioral finance and noise traders: A review and assessment of the literature," International Review of Financial Analysis, Elsevier, vol. 41(C), pages 89-100.
    12. Smales, L.A., 2021. "Investor attention and global market returns during the COVID-19 crisis," International Review of Financial Analysis, Elsevier, vol. 73(C).
    13. Chen, Zhongdong & Craig, Karen Ann, 2023. "Active attention, retail investor base, and stock returns," Journal of Behavioral and Experimental Finance, Elsevier, vol. 39(C).
    14. Sifat, Imtiaz Mohammad & Thaker, Hassanudin Mohd Thas, 2020. "Predictive power of web search behavior in five ASEAN stock markets," Research in International Business and Finance, Elsevier, vol. 52(C).
    15. Tripathi, Abhinava & Pandey, Ashish, 2021. "Information dissemination across global markets during the spread of COVID-19 pandemic," International Review of Economics & Finance, Elsevier, vol. 74(C), pages 103-115.
    16. Chou, Pin-Huang & Huang, Tsung-Yu & Yang, Hung-Jeh, 2013. "Arbitrage risk and the turnover anomaly," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4172-4182.
    17. Ramos, Sofia B. & Latoeiro, Pedro & Veiga, Helena, 2020. "Limited attention, salience of information and stock market activity," Economic Modelling, Elsevier, vol. 87(C), pages 92-108.
    18. Desagre, Christophe & D’Hondt, Catherine, 2021. "Googlization and retail trading activity," Journal of Behavioral and Experimental Finance, Elsevier, vol. 29(C).
    19. Halousková, Martina & Stašek, Daniel & Horváth, Matúš, 2022. "The role of investor attention in global asset price variation during the invasion of Ukraine," Finance Research Letters, Elsevier, vol. 50(C).
    20. Daniel Chai & Mengjia Dai & Philip Gharghori & Barbara Hong, 2021. "Internet Search Intensity and Its Relation with Trading Activity and Stock Returns," International Review of Finance, International Review of Finance Ltd., vol. 21(1), pages 282-311, March.

    More about this item

    Keywords

    Attention measures; Smart investors; Noise traders; Price pressure hypothesis; Behavioral finance;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G4 - Financial Economics - - Behavioral Finance

    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:ecmode:v:83:y:2019:i:c:p:141-149. 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/30411 .

    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.