New technical indicators and stock returns predictability

Zhifeng Dai, Huan Zhu and Jie Kang

International Review of Economics & Finance, 2021, vol. 71, issue C, 127-142

Abstract: We find that combining de-noising stock returns by wavelet transform with new proposed technical indicators can significantly improve the accuracy of stock returns forecasts, in which the new technical indicators can directly reflect the trend of stock returns series. Empirical results indicate the stock returns forecasts generated by new technical indicators are statistically and economically significant both in-sample and out-of-sample prediction performance. And when multivariate information is used to predict stock returns, its predictability is also significant. In addition, it is robust for the prediction performance of new indicators using some extension and robustness analysis.

Keywords: New technical indicators; De-noise; In-sample forecast; Out-of-sample forecast; Economic significance (search for similar items in EconPapers)
JEL-codes: C11 C22 G11 G12 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (14)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reveco:v:71:y:2021:i:c:p:127-142

DOI: 10.1016/j.iref.2020.09.006

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