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Exchange rate predictability: Fact or fiction?

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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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    2. Yin-Wong Cheung & Wenhao Wang & Frank Westermann, 2025. "An In-Sample Evaluation of Exchange Rate Models: In Search of Scapegoats," IEER Working Papers 125, Institute of Empirical Economic Research, Osnabrueck University.
    3. Uluc Aysun & Melanie Guldi, 2026. "Revisiting exchange rate predictability: Can machine learning with theoretical filtering outperform canonical models?," Working Papers 2026-01, University of Central Florida, Department of Economics.
    4. Dai, Xingyu & Yousaf, Imran & Wang, Jiqian & Wang, Qunwei & Lau, Chi Keung Marco, 2025. "The pass-through of macro variable to volatility co-movement among U.S. currency and commodity futures markets system," Journal of Commodity Markets, Elsevier, vol. 38(C).

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    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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