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Google Search in Exchange Rate Models: Hype or Hope?

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  • Bodo Herzog

    (Economics Department, ESB Business School, Reutlingen University, 72762 Reutlingen, Germany
    Reutlingen Research Institute (RRI), Reutlingen University, 72762 Reutlingen, Germany
    Institute of Finance and Economics (IFE), Reutlingen University, 72762 Reutlingen, Germany)

  • Lana dos Santos

    (Economics Department, ESB Business School, Reutlingen University, 72762 Reutlingen, Germany)

Abstract

This paper studies the power of online search intensity metrics, measured by Google, for examining and forecasting exchange rates. We use panel data consisting of quarterly time series from 2004 to 2018 and ten international countries with the highest currency trading volume. Newly, we include various Google search intensity metrics to our panel data. We find that online search improves the overall econometric models and fits. First, four out of ten search variables are robustly significant at one percent and enhance the macroeconomic exchange rate models. Second, country regressions corroborate the panel results, yet the predictive power of search intensity with regard to exchange rates vary by country. Third, we find higher prediction performance for our exchange rate models with search intensity, particularly in regard to the direction of the exchange rate. Overall, our approach reveals a value-added of search intensity in exchange rate models.

Suggested Citation

  • Bodo Herzog & Lana dos Santos, 2021. "Google Search in Exchange Rate Models: Hype or Hope?," JRFM, MDPI, vol. 14(11), pages 1-40, October.
    • Handle: RePEc:gam:jjrfmx:v:14:y:2021:i:11:p:512-:d:664517
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