Warwick Business School Financial Econometrics Research Centre
Abstract
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
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