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Multiple-Predictor Regressions: Hypothesis Testing

delete2008-06-13
delete94
PRE
AI
Y
Yakov Amihud *
C
Clifford M. Hurvich
王
王怡 (Yi Wang)
DOI：10.1093/rfs/hhn056delete
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摘要

摘要

En 中文
We propose a new hypothesis-testing method for multipredictor regressions in small samples, where the dependent variable is regressed on lagged variables that are autoregressive. The new test is based on the augmented regression method (Amihud and Hurvich, 2004), which produces reduced-bias coefficients and is easy to implement. The method's usefulness is demonstrated by simulations and by testing a model where stock returns are predicted by two variables, income-to-consumption and dividend yield.
Keyword:
STOCK
RETURNS
INFERENCE
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期刊

Review of Financial Studies 封面图
Review of Financial Studies
IF:
5.4
论文数:
2.8K
被引数:
3.0W

机构

N
New York University
学者数:
4.4W
论文数: 3.9W
被引数: 5.8W
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