Exchange rate predictability: Fact or fiction?

Karen Jackson and Georgios Magkonis

Journal of International Money and Finance, 2024, vol. 142, issue C

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.

Keywords: Exchange rates; Forecasting performance; Meta-analysis (search for similar items in EconPapers)
JEL-codes: C83 F31 F37 (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:jimfin:v:142:y:2024:i:c:s0261560624000135

DOI: 10.1016/j.jimonfin.2024.103026

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