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Understanding Spurious Regression in Financial Economics

Ai Deng ()

Journal of Financial Econometrics, 2014, vol. 12, issue 1, 122-150

Abstract: 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.

Keywords: spurious regression; signal-to-noise ratio; fixed-b asymptotics; data mining; stock return predictability (search for similar items in EconPapers)
JEL-codes: C12 C13 C22 G17 (search for similar items in EconPapers)
Date: 2014
References: View complete reference list from CitEc
Citations: View citations in EconPapers (4) Track citations by RSS feed

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