Forecasting Foreign Exchange Markets Using Google Trends: Prediction Performance of Competing Models.
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| Title: | Forecasting Foreign Exchange Markets Using Google Trends: Prediction Performance of Competing Models. |
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| Authors: | Wilcoxson, Jordan (AUTHOR), Follett, Lendie (AUTHOR), Severe, Sean (AUTHOR) |
| Source: | Journal of Behavioral Finance. Oct-Dec2020, Vol. 21 Issue 4, p412-422. 11p. |
| Subjects: | Foreign exchange market, Foreign exchange rates, Forecasting |
| Geographic Terms: | United States |
| Abstract: | Foreign exchange markets affect a variety of humans and businesses worldwide and there is a wide array of literature aimed at providing more accurate forecasts of their movement. In an attempt to quantify human expectations, Google query search terms related to foreign exchange markets are used to help explain and predict foreign exchange rates between the United States' dollar and ten other currencies during the time period of January 2004 and August 2018. We find evidence that, while Google Trends can be helpful in prediction, it is necessary to implement some sort of shrinkage or sparsity scheme on the coefficients. [ABSTRACT FROM AUTHOR] |
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| Database: | Psychology and Behavioral Sciences Collection |
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| Abstract: | Foreign exchange markets affect a variety of humans and businesses worldwide and there is a wide array of literature aimed at providing more accurate forecasts of their movement. In an attempt to quantify human expectations, Google query search terms related to foreign exchange markets are used to help explain and predict foreign exchange rates between the United States' dollar and ten other currencies during the time period of January 2004 and August 2018. We find evidence that, while Google Trends can be helpful in prediction, it is necessary to implement some sort of shrinkage or sparsity scheme on the coefficients. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 15427560 |
| DOI: | 10.1080/15427560.2020.1716233 |
