Journal
JOURNAL OF FINANCIAL ECONOMETRICS
Volume 12, Issue 1, Pages 122-150Publisher
OXFORD UNIV PRESS
DOI: 10.1093/jjfinec/nbs025
Keywords
spurious regression; signal-to-noise ratio; fixed-b asymptotics; data mining; stock return predictability
Categories
Ask authors/readers for more resources
A new asymptotic framework is used to provide finite sample approximations for various statistics in the spurious return predictive regression analyzed by Ferson, Sarkissian, and Simin (2003a). Our theory explains all the findings of Ferson, Sarkissian, and Simin (2003a) and confirms the theoretical possibility of a spurious regression bias. The theory developed in the article has important implications with respect to existing inferential theories in predictive regressions. We also propose a simple diagnostic test to detect potential spurious regression bias in empirical analysis. The test is applied to four variants of the SP500 monthly stock returns and the six Fama-French benchmark portfolio monthly returns.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available