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Can Internet Search Queries Help to Predict Stock Market Volatility?

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  • Thomas Dimpfl
  • Stephan Jank

Abstract

We study the dynamics of stock market volatility and retail investors' attention to the stock market. The latter is measured by internet search queries related to the leading stock market index. We find a strong co†movement of the Dow Jones' realised volatility and the volume of search queries for its name. Furthermore, search queries Granger†cause volatility: a heightened number of searches today is followed by an increase in volatility tomorrow. Including search queries in autoregressive models of realised volatility improves volatility forecasts in†sample, out†of†sample, for different forecasting horizons, and in particular in high†volatility phases.

Suggested Citation

  • Thomas Dimpfl & Stephan Jank, 2016. "Can Internet Search Queries Help to Predict Stock Market Volatility?," European Financial Management, European Financial Management Association, vol. 22(2), pages 171-192, March.
    • Handle: RePEc:bla:eufman:v:22:y:2016:i:2:p:171-192
    DOI: 10.1111/eufm.12058
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    More about this item

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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