Testing the Predictability of Stock Returns
指出以往文献中股票收益可被强自相关变量预测的发现可能是虚假的，源于忽略近单位根问题，并提出一种新检验方法。使用该检验，1928-1996年美国股票收益数据未发现可预测性。
Previous literature indicates that stock returns are predictable by several strongly autocorrelated forecasting variables, especially at longer horizons. It is suggested that this finding is spurious and follows from a neglected near unit root problem. Instead of the commonly used t-test, we propose a test that can be considered as a general test of whether the return can be predicted by any highly persistent variable. Using this test, no predictability is found for U.S. stock return data from the period 1928-1996. Simulation experiments show that the standard t-test clearly overrejects whereas our proposed test controls size much better. © 2002 by the President and Fellows of Harvard College and the Massachusetts Institute of Technology