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 vario...
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2021
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oai:doaj.org-article:0f89b3554b6a482e9f7ebc2d1cf488162021-11-25T18:08:26ZGoogle Search in Exchange Rate Models: Hype or Hope?10.3390/jrfm141105121911-80741911-8066https://doaj.org/article/0f89b3554b6a482e9f7ebc2d1cf488162021-10-01T00:00:00Zhttps://www.mdpi.com/1911-8074/14/11/512https://doaj.org/toc/1911-8066https://doaj.org/toc/1911-8074This 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.Bodo HerzogLana dos SantosMDPI AGarticleexchange rateGoogle searchbig dataAIinformation inattentionRisk in industry. Risk managementHD61FinanceHG1-9999ENJournal of Risk and Financial Management, Vol 14, Iss 512, p 512 (2021) |
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exchange rate Google search big data AI information inattention Risk in industry. Risk management HD61 Finance HG1-9999 Bodo Herzog Lana dos Santos Google Search in Exchange Rate Models: Hype or Hope? |
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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. |
format |
article |
author |
Bodo Herzog Lana dos Santos |
author_facet |
Bodo Herzog Lana dos Santos |
author_sort |
Bodo Herzog |
title |
Google Search in Exchange Rate Models: Hype or Hope? |
title_short |
Google Search in Exchange Rate Models: Hype or Hope? |
title_full |
Google Search in Exchange Rate Models: Hype or Hope? |
title_fullStr |
Google Search in Exchange Rate Models: Hype or Hope? |
title_full_unstemmed |
Google Search in Exchange Rate Models: Hype or Hope? |
title_sort |
google search in exchange rate models: hype or hope? |
publisher |
MDPI AG |
publishDate |
2021 |
url |
https://doaj.org/article/0f89b3554b6a482e9f7ebc2d1cf48816 |
work_keys_str_mv |
AT bodoherzog googlesearchinexchangeratemodelshypeorhope AT lanadossantos googlesearchinexchangeratemodelshypeorhope |
_version_ |
1718411542877175808 |