This analysis evaluates exchange rate forecasting effectiveness in hyperinflation, suggesting fundamental models can improve predictions.
The Meese–Rogoff puzzle suggests that exchange rate models rarely outperform a random walk in out-of-sample forecasting. This paper re-examines that puzzle in the context of the German hyperinflation, an environment in which monetary forces dominate economic behavior. Using simple bivariate specifications derived from the quantity theory of money, purchasing power parity, and the monetary model of exchange rates, the paper evaluates forecasting performance against a random walk benchmark. The results show that during the most intense phase of hyperinflation, these fundamentals-based models can outperform the random walk in terms of root mean square error. This finding indicates that exchange rate predictability is regime-dependent and that, under extreme monetary instability, basic theoretical relationships can regain forecasting power.
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Mohammad Alawin (2026) studied this question.
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