Google Trends and Forecasting Performance of Exchange Rate Models

Author(s):  
Levent Bulut
2019 ◽  
Vol 24 (02) ◽  
Author(s):  
L. Espinoza-Audelo ◽  
E. Aviles-Ochoa ◽  
E. Leon-Castro ◽  
F. Blanco-Mesa

2018 ◽  
Vol 14 (2) ◽  
Author(s):  
Levent Bulut ◽  
Can Dogan

Abstract In this paper, we use Google Trends data to proxy macro fundamentals that are related to two conventional structural determination of exchange rate models: purchasing power parity model and the monetary exchange rate determination model. We assess forecasting performance of Google Trends based models against random walk null on Turkish Lira–US Dollar exchange rate for the period of January 2004 to August 2015. We offer a three-step methodology for query selection for macro fundamentals in Turkey and the US. In out-of-sample forecasting, results show better performance against no-change random walk predictions for specifications both when we use Google Trends data as the only exchange rate predictor or augment it with exchange rate fundamentals. We also find that Google Trends data has limited predictive power when used in year-on-year growth rate format.


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