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Predictable Stock Returns: The Role of Small Sample Bias
Author(s) -
NELSON CHARLES R.,
KIM MYUNG J.
Publication year - 1993
Publication title -
the journal of finance
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 18.151
H-Index - 299
eISSN - 1540-6261
pISSN - 0022-1082
DOI - 10.1111/j.1540-6261.1993.tb04731.x
Subject(s) - predictability , econometrics , inference , stock (firearms) , statistics , standard error , mathematics , economics , computer science , geography , archaeology , artificial intelligence
Predictive regressions are subject to two small sample biases: the coefficient estimate is biased if the predictor is endogenous, and asymptotic standard errors in the case of overlapping periods are biased downward. Both biases work in the direction of making t ‐ratios too large so that standard inference may indicate predictability even if none is present. Using annual returns since 1872 and monthly returns since 1927 we estimate empirical distributions by randomizing residuals in the VAR representation of the variables. The estimated biases are large enough to affect inference in practice, and should be accounted for when studying predictability.