Predictability in International Asset Returns: A Reexamination
指出，基于较短时间序列数据的向量自回归模型推断长期资产收益可预测性可能不可靠。通过重新检验Bekaert和Hodrick（1992）的研究，发现样本外预测效果差，简单基准模型更优，且数据可能并非由稳定的VAR生成。
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.