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Google search in exchange rate models : hype or hope?

  • 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.

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Metadaten
Author of HS ReutlingenHerzog, Bodo; dos Santos, Lana
URN:urn:nbn:de:bsz:rt2-opus4-32548
DOI:https://doi.org/10.3390/jrfm14110512
ISSN:1911-8066
eISSN:1911-8074
Erschienen in:Journal of risk and financial management : JRFM
Publisher:MDPI
Place of publication:Basel
Document Type:Article
Language:English
Year of Publication:2021
Tag:AI; Google search; big data; exchange rate; information inattention
Volume:14
Issue:11
Page Number:40
First Page:1
Last Page:40
Article Number:512
DDC classes:650 Management
Open Access?:Ja
Licence (German):License Logo  Creative Commons - CC BY - Namensnennung 4.0 International