The Out-of-Sample Success of Term Structure Models as Exchange Rate Predictors: A Step Beyond

Working Paper: NBER ID: w8601

Authors: Richard H. Clarida; Lucio Sarno; Mark P. Taylor; Giorgio Valente

Abstract: A large literature suggests that standard exchange rate models cannot outperform a random walk forecast and that the forward rate is not an optimal predictor of the spot rate. However, there is evidence that the term structure of forward premia contains valuable information for forecasting future spot exchange rates and that exchange rate dynamics display nonlinearities. This paper proposes a term-structure forecasting model of exchange rates based on a regime-switching vector equilibrium correction model which is novel in this context. Our model significantly outperforms both a random walk and a linear term-structure vector equilibrium correction model for four major dollar rates across a range of horizons.

Keywords: exchange rates; term structure models; forecasting

JEL Codes: F31; F37


Causal Claims Network Graph

Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.


Causal Claims

CauseEffect
forward premia (G19)spot exchange rate forecasts (F31)
nonlinear MSVECM (C32)accuracy of exchange rate predictions (F31)
term structure (E43)exchange rate forecasting (F37)

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