Google Search Intensity and the Investor Attention Effect: A Quantile Regression Approach

Abstract

This paper investigates whether the investor attention effect caused by the Google stock search can be used to forecast stock returns. The evolving literature on Google search investor attention effect suggests that high Google search volumes can predict high returns for the first 1–2 weeks, but with a subsequent price reversal. We use a more recent data set that covers the period from 2012 to 2017 in the Indian stock market and employ the quantile regression approach as it alleviates some of the statistical problems to find that high Google search volumes lead to positive returns. Indeed, the high Google search volumes predict positive and significant returns in the subsequent third, fourth and fifth weeks. The Google search volume index performs as a better predictor of the direction as well as the magnitude of the excess returns. The findings infer that the signals from the search volume data could be of benefit construction of profitable trading strategies.

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Notes

  1. 1.

    Quantile regression analyses can be easily implemented using commercial statistics software such as Eviews, Stata and SAS. Koenker and Hallock (2001) provide a brilliant introduction to quantile regression.

  2. 2.

    In the OLS method, the conditional mean relationship is the estimation of the mean value of the dependent variable given a fixed value of each explanatory variable. On the contrary, in the QReg method, given a fixed value of each explanatory variable, various percentiles of the distribution of the dependent variables, e.g., 10, 25, 50, 75, and 90% percentiles are estimated. Koenker and Hallock’s (2001) provide an excellent survey on quantile regression and a discussion of the intuition behind the class of estimators.

  3. 3.

    The NIFTY 50 is a diversified 50 stock index accounting for 12 sectors of the economy. It is used for a variety of purposes such as benchmarking fund portfolios, index based derivatives and index funds. The NIFTY 50 Index represents about 62.9% of the free float market capitalization of the stocks listed on NSE as on March 31, 2017. The total traded value of NIFTY 50 index constituents for the last 6 months ending March 2017 is approximately 43.8% of the traded value of all stocks on the NSE. (source: https://www.nseindia.com/products/content/equities/indices/nifty_50.htm.

  4. 4.

    The data on the online search intensity is obtained from Google Trends (http://www.google.co.in/trends/).

  5. 5.

    The results of the Slope Equality test are not reported here in the interest of space. But they are available on request for verification.

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Correspondence to Vighneswara Swamy.

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Swamy, V., Dharani, M. Google Search Intensity and the Investor Attention Effect: A Quantile Regression Approach. J. Quant. Econ. 18, 403–423 (2020). https://doi.org/10.1007/s40953-019-00185-9

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Keywords

  • Stock returns
  • Google searches
  • Investor attention/sentiment
  • Trading strategies
  • Quantile regression

JEL Classification

  • G11
  • G12
  • G14