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Exchange rate predictability: Fact or fiction?

Author

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  • Jackson, Karen
  • Magkonis, Georgios

Abstract

The present study investigates the factors that affect the forecasting performance of several models that have been used for exchange rate prediction. We provide a quantitative survey collecting 8,413 reported forecast errors and we investigate which forecasting characteristics tend to improve forecasting ability. According to our evidence, predictions can beat random walk when certain types of models and econometric methods are used. In particular, linear specifications based on PPP outperform random walk. Furthermore, higher data frequency and longer forecasting horizon also improve forecasting performance. In this way, we identify under which conditions it is feasible to solve the ‘Meese-Rogoff’ puzzle.

Suggested Citation

  • Jackson, Karen & Magkonis, Georgios, 2024. "Exchange rate predictability: Fact or fiction?," Journal of International Money and Finance, Elsevier, vol. 142(C).
    • Handle: RePEc:eee:jimfin:v:142:y:2024:i:c:s0261560624000135
    DOI: 10.1016/j.jimonfin.2024.103026
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    More about this item

    Keywords

    Exchange rates; Forecasting performance; Meta-analysis;
    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
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods

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