Google Trends and Structural Exchange Rate Models for Turkish Lira–US Dollar Exchange Rate

Levent Buluthttp://orcid.org/0000-0003-1662-2050 1  and Can Dogan 2
  • 1 Valdosta State University, Harley Langdale, Jr. College of Business Administration, Department of Economics and Finance, Valdosta, United States of America
  • 2 College of Business and Economics, Department of Economics, Radford University, Radford, USA
Levent BulutORCID iD: http://orcid.org/0000-0003-1662-2050 and 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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The Review of Middle East Economics and Finance (RMEEF) addresses applied original research in the fields of economics and finance pertaining to the MENA region (Middle East and North Africa), including Turkey and Iran. The journal also publishes articles that deal with the economies of neighboring countries and/or the relationship and interactions between those economies and the MENA region.

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