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The Impact of Internet Information Flow Regarding ‘Innovation’ on Common Stock Returns: Volume vs Google Search Quarries

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  • Senarathne Chamil W.

    (School of Economics, Wuhan University of Technology, 122 Luoshi Road, Wuhan, Hubei, 430070, P.R.China)

Abstract

A number of scholars examine the impact of information flow associated with Google search queries of various search terms on heteroskedasticity of stock return data using the framework of Lamoureux and Lastrapes (1990). This paper examines the role of internet search queries in carrying the new information flow regarding economic innovation to the stock market for ten countries from a sample of top twenty innovative counties (based on Global Innovation Index 2018). When the internet search volume is included in the conditional variance equation of GJR-GRACH model, the ARCH coefficient becomes statistically insignificant for Canada, South Korea, Switzerland and USA (Hong Kong and South Korea to some extent). These findings suggest that the number of internet search volume is a manifestation of residual heteroskedasticity (ARCH type) in stock return data. As such, the internet provides a much-needed infrastructure for carrying the new information flow attached to economic innovation to the stock market as the common stockholder (i.e. capital providers for innovation) expectations reflect such persistent flow of new knowledge to the stock market. Trading volume testifies the specification used and, as such, the internet search queries could possibly be interpreted as an absorptive capacity variable as stock of new knowledge flow of the economy could be successfully traced by volume.

Suggested Citation

  • Senarathne Chamil W., 2019. "The Impact of Internet Information Flow Regarding ‘Innovation’ on Common Stock Returns: Volume vs Google Search Quarries," Management of Sustainable Development, Sciendo, vol. 11(1), pages 43-49, June.
  • Handle: RePEc:vrs:msudev:v:11:y:2019:i:1:p:43-49:n:7
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    Keywords

    Innovation; Information Flow; GJR-GARCH; Volume; Google Search Queries; Heteroskedasticity; Conditional Variance; Mixture of Distributions Hypothesis;
    All these keywords.

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D53 - Microeconomics - - General Equilibrium and Disequilibrium - - - Financial Markets
    • E51 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Money Supply; Credit; Money Multipliers
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives

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