Predictability in International Asset Returns: A Reexamination
Christopher J. Neely
Federal Reserve Bank of St. Louis - Research Division
Paul A. Weller
University of Iowa - Department of Finance
Journal of Financial and Quantitative Analysis, Vol. 35, No. 4, December 2000
This paper argues that inferring long-horizon asset-return predictability from the properties of vector autoregressive (VAR) models on relatively short spans of data is potentially unreliable. We illustrate the problems that can arise by re-examining the findings of Bekaert and Hodrick (1992), who detected evidence of in-sample predictability in international equity and foreign exchange markets using VAR methodology for a variety of countries over the period 1981-1989. The VAR predictions are significantly biased in most out-of-sample forecasts and are conclusively outperformed by a simple benchmark model at horizons of up to six months. This remains true even after corrections for small sample bias and the introduction of Bayesian parameter restrictions. A Monte Carlo analysis indicates that the data are unlikely to have been generated by a stable VAR. This conclusion is supported by an examination of structural break statistics. Implied long-horizon statistics calculated from the VAR parameter estimates are shown to be very unreliable.
Keywords: Vector autoregression, asset price, exchange rate, forecasting
JEL Classification: C32, F30
Date posted: January 5, 2001
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