IDEAS home Printed from https://ideas.repec.org/a/sos/sosjrn/200209.html
   My bibliography  Save this article

The Effect of Investor Attention on Equity Markets: Panel Data Analysis on Banks Traded on Borsa Istanbul

Author

Listed:
  • Tuğba NUR-TOPALOĞLU
  • İlhan EGE

Abstract

In this study, it is aimed to investigate the relationship between investor’s attention measured by SVI (Google Search Volume Index) and both stock return and trading volume of the banks listed in Borsa İstanbul for the period 2010-2018. For this purpose, together with “bank name stock”, “bank name stock market”, “banks’ BIST code” keyword search volumes, “Total GAT” which is the sum of the each independent search volume index has been taken as independent variables while stock returns and trading volume are used as dependent variables. As a result of the panel data analysis, a statistically significant and positive relationship has been found between stock return and the “banks’ BIST code”, while no significant relationship has been found between other independent variables and the stock return. In addition, while there exists a statistically significant and positive relationship between each of the independent variables namely “bank name stock market”, “banks’ BIST code”, “total GAT” and our other dependent variable, trading volume, there is no statistically significant relationship between “bank name stock” variable and trading volume. The results of this research are generally supported by Merton (1987) Investor Recognition Hypothesis and Barber and Odean (2008) Price Pressure Hypothesis.

Suggested Citation

  • Tuğba NUR-TOPALOĞLU & İlhan EGE, 2020. "The Effect of Investor Attention on Equity Markets: Panel Data Analysis on Banks Traded on Borsa Istanbul," Sosyoekonomi Journal, Sosyoekonomi Society, issue 28(44).
  • Handle: RePEc:sos:sosjrn:200209
    as

    Download full text from publisher

    File URL: http://dergipark.gov.tr/download/article-file/1060175
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. A. Bhargava & L. Franzini & W. Narendranathan, 2006. "Serial Correlation and the Fixed Effects Model," World Scientific Book Chapters, in: Econometrics, Statistics And Computational Approaches In Food And Health Sciences, chapter 4, pages 61-77, World Scientific Publishing Co. Pte. Ltd..
    2. Jushan Bai & Serena Ng, 2004. "A PANIC Attack on Unit Roots and Cointegration," Econometrica, Econometric Society, vol. 72(4), pages 1127-1177, July.
    3. Brad M. Barber & Terrance Odean, 2001. "Boys will be Boys: Gender, Overconfidence, and Common Stock Investment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 116(1), pages 261-292.
    4. 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.
    5. Baltagi, Badi H. & Li, Qi, 1991. "A joint test for serial correlation and random individual effects," Statistics & Probability Letters, Elsevier, vol. 11(3), pages 277-280, March.
    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. Baltagi, Badi H. & Li, Qi, 1995. "Testing AR(1) against MA(1) disturbances in an error component model," Journal of Econometrics, Elsevier, vol. 68(1), pages 133-151, July.
    2. repec:jss:jstsof:27:i02 is not listed on IDEAS
    3. Croissant, Yves & Millo, Giovanni, 2008. "Panel Data Econometrics in R: The plm Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 27(i02).
    4. González-Fernández, Marcos & González-Velasco, Carmen, 2020. "A sentiment index to measure sovereign risk using Google data," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 406-418.
    5. Benjamin Born & Jörg Breitung, 2016. "Testing for Serial Correlation in Fixed-Effects Panel Data Models," Econometric Reviews, Taylor & Francis Journals, vol. 35(7), pages 1290-1316, August.
    6. Desagre, Christophe & D’Hondt, Catherine, 2021. "Googlization and retail trading activity," Journal of Behavioral and Experimental Finance, Elsevier, vol. 29(C).
    7. Nagayasu, Jun & Inakura, Noriko, 2009. "PPP: Further evidence from Japanese regional data," International Review of Economics & Finance, Elsevier, vol. 18(3), pages 419-427, June.
    8. Li, Si & Perez, M. Fabricio, 2021. "The evolution of pay premiums for managerial attributes," Journal of Corporate Finance, Elsevier, vol. 69(C).
    9. Berg, Joyce E. & Rietz, Thomas A., 2019. "Longshots, overconfidence and efficiency on the Iowa Electronic Market," International Journal of Forecasting, Elsevier, vol. 35(1), pages 271-287.
    10. Arturas Juodis, 2013. "Cointegration Testing in Panel VAR Models Under Partial Identification and Spatial Dependence," UvA-Econometrics Working Papers 13-08, Universiteit van Amsterdam, Dept. of Econometrics.
    11. Nagayasu, Jun, 2010. "Macroeconomic interdependence in East Asia," Japan and the World Economy, Elsevier, vol. 22(4), pages 219-227, December.
    12. Maxime Menuet & Petros G. Sekeris, 2021. "Overconfidence and conflict," Economic Inquiry, Western Economic Association International, vol. 59(4), pages 1483-1499, October.
    13. Mariam Camarero & Juan Sapena & Cecilio Tamarit, 2020. "Modelling Time-Varying Parameters in Panel Data State-Space Frameworks: An Application to the Feldstein–Horioka Puzzle," Computational Economics, Springer;Society for Computational Economics, vol. 56(1), pages 87-114, June.
    14. Siganos, Antonios, 2013. "Google attention and target price run ups," International Review of Financial Analysis, Elsevier, vol. 29(C), pages 219-226.
    15. Daniel Fonseca Costa & Francisval Carvalho & Bruno César Moreira & José Willer Prado, 2017. "Bibliometric analysis on the association between behavioral finance and decision making with cognitive biases such as overconfidence, anchoring effect and confirmation bias," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1775-1799, June.
    16. Bobba, Matteo & Frisancho, Veronica, 2022. "Self-perceptions about academic achievement: Evidence from Mexico City," Journal of Econometrics, Elsevier, vol. 231(1), pages 58-73.
    17. Claudio Morana, 2010. "Heteroskedastic Factor Vector Autoregressive Estimation of Persistent and Non Persistent Processes Subject to Structural Breaks," ICER Working Papers - Applied Mathematics Series 36-2010, ICER - International Centre for Economic Research.
    18. 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.
    19. Claudio Morana, 2014. "Factor Vector Autoregressive Estimation of Heteroskedastic Persistent and Non Persistent Processes Subject to Structural Breaks," Working Papers 273, University of Milano-Bicocca, Department of Economics, revised May 2014.
    20. Jason M. Lindo & Nicholas J. Sanders & Philip Oreopoulos, 2010. "Ability, Gender, and Performance Standards: Evidence from Academic Probation," American Economic Journal: Applied Economics, American Economic Association, vol. 2(2), pages 95-117, April.
    21. Cem Ertur & Antonio Musolesi, 2017. "Weak and Strong Cross‐Sectional Dependence: A Panel Data Analysis of International Technology Diffusion," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(3), pages 477-503, April.

    More about this item

    Keywords

    Investor Attention; Google Search Trends; Equity Market.;
    All these keywords.

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • G2 - Financial Economics - - Financial Institutions and Services
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

    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:sos:sosjrn:200209. 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: Aysen Sivrikaya (email available below). General contact details of provider: http://www.sosyoekonomijournal.org/home.html .

    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.