02276cam a22002417 4500001000600000003000500006005001700011008004100028100002300069245012400092260006600216490004100282500001600323520132700339530006101666538007201727538003601799700001801835710004201853830007601895856003701971856002602008w3297NBER20140728153914.0140728s1990 mau||||fs|||| 000 0 eng d1 aNelson, Charles R.10aPredictable Stock Returnsh[electronic resource]:bReality or Statistical Illusion? /cCharles R. Nelson, Myung J. Kim. aCambridge, Mass.bNational Bureau of Economic Researchc1990.1 aNBER working paper seriesvno. w3297 aMarch 1990.3 aRecent research suggests that stock returns are predictable from fundamentals such as dividend yield, and that the degree of predictability rises with the length of the horizon over which return is measured. This paper investigates the magnitude of two sources of small simple bias in these results. First, it is a standard result in econometrics that regression on the lagged value of the dependent variable is biased in finite samples. Since a fundamental such as the price/dividend ratio is a statistical proxy for lagged price, predictive regressions are potentially subject to a corresponding small sample bias. This may create the illusion that one can buy low and sell high in the sample even if the relationship is useless for forecasting. Second, multiperiod returns are positively autocorrelated by construction, raising the possibility of spurious regression. Standard errors which are computed from the asymptotic formula may not be large enough in small samples. A set of Monte Carlo experiments are presented in which data are generated by a version of the present value model in which the discount rate is constant so returns are not in fact predictable. We show that a number of the characteristica of the historical results can be replicated simply by the combined effects of the two small sample biases. aHardcopy version available to institutional subscribers. aSystem requirements: Adobe [Acrobat] Reader required for PDF files. aMode of access: World Wide Web.1 aKim, Myung J.2 aNational Bureau of Economic Research. 0aWorking Paper Series (National Bureau of Economic Research)vno. w3297.4 uhttp://www.nber.org/papers/w3297 uurn:doi:10.3386/w3297