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

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  • 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
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    References listed on IDEAS

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    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.
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    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

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