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Google Trends and Forecasting Performance of Exchange Rate Models

Author

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  • Levent Bulut

    (Department of Economics, Ipek University)

Abstract

In this paper, internet search data provided from Google Trends is utilized to nowcast the known variates of alternative exchange rate determination models. The sample covers 12 OECD countries’ exchange rates for the period from Jan 2004 to June 2014. The results indicate that inclusion of Google Trends-based nowcasting values of macro fundamentals to the current set of government released-macro-economic variables improve the out-of-sample forecast of Purchasing Power Parity model in seven currency pairs and of Monetary model in four currency pairs. In this paper we claim that, for proper testing of the structural models, since there is a lag in the release of official data on macro fundamentals, the literature should focus more on using ex ante variables on current macro fundamentals and nowcasting of these variables with utilization of Google Search Inquiries can be one alternative for this purpose.

Suggested Citation

  • Levent Bulut, 2015. "Google Trends and Forecasting Performance of Exchange Rate Models," IPEK Working Papers 1505, Ipek University, Department of Economics.
    • Handle: RePEc:ipk:wpaper:1505
    as

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    File URL: http://econpapers.ipek.edu.tr/IpekWParchives/wp2015/wp1505Bulut.pdf
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    References listed on IDEAS

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    More about this item

    Keywords

    Meese-Rogoff Puzzle; Out-of-sample predictability of Exchange Rates; Google Trends;
    All these keywords.

    JEL classification:

    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • F37 - International Economics - - International Finance - - - International Finance Forecasting and Simulation: Models and Applications
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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