Technical analysis and stock return predictability: An aligned approach

Qi Lin

Journal of Financial Markets, 2018, vol. 38, issue C, 103-123

Abstract: This paper provides an empirical evaluation of the U.S. aggregate stock market predictability based on a new technical analysis index that eliminates the idiosyncratic noise component in technical indicators. I find that the new index exhibits statistically and economically significant in-sample and out-of-sample predictive power and outperforms the well-known technical indicators and macroeconomic variables. In addition, it can predict cross-sectional stock portfolio returns sorted by size, value, momentum, and industry and generate substantial utility gains for a mean-variance investor. A vector autoregression-based stock return decomposition shows that the economic source of the predictive power predominantly comes from time variations in future cash flows (i.e., the cash flow channel).

Keywords: Technical analysis; Equity risk premium; Partial least squares method; Predictive regression; Cash flow channel (search for similar items in EconPapers)
JEL-codes: C53 G11 G12 G14 (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (46)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:finmar:v:38:y:2018:i:c:p:103-123

DOI: 10.1016/j.finmar.2017.09.003

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