A frequency-domain alternative to long-horizon regressions with application to return predictability

Natalia Sizova

Journal of Empirical Finance, 2014, vol. 28, issue C, 261-272

Abstract: This paper aims at improved accuracy in testing for long-run predictability in noisy series, such as stock market returns. Long-horizon regressions have previously been the dominant approach in this area. We suggest an alternative method that yields more accurate results. We find evidence of predictability in S&P 500 returns even when the confidence intervals are constructed using model-free methods based on subsampling.

Keywords: Predictive regression; Semiparametric method; Local-to-unity; Long memory; Long-horizon regression; Subsampling (search for similar items in EconPapers)
JEL-codes: C12 C14 E47 G12 G14 (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:empfin:v:28:y:2014:i:c:p:261-272

DOI: 10.1016/j.jempfin.2014.03.002

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