Exploring the nonlinear idiosyncratic volatility puzzle: evidence from China

Sabri Boubaker; Zhenya Liu; Waël   Louhichi; Yao Yao

doi:10.1007/s10614-022-10265-3

Exploring the nonlinear idiosyncratic volatility puzzle: evidence from China

Sabri Boubaker, Zhenya Liu^*, Waël Louhichi, Yao Yao

^*Corresponding author for this work

Economics

Research output: Contribution to journal › Article › peer-review

Abstract

This paper studies the spectrum of the idiosyncratic volatility (IVOL) puzzle in the Chinese A-share market using functional data analysis (FDA). It highlights a nonlinear IVOL puzzle with a steady reduction in the bottom 20% of average returns and a large drop of 1% in the top 10%, consistent with the herding, certainty, and reflection effects in China’s A-share markets. Furthermore, empirical evidence suggests that the FDA technique has a 30% greater goodness of fit than linear regressions, suggesting that nonlinearity plays a non-negligible role in the IVOL puzzle. These results can be useful for investors and hedgers, as they show that stock returns decline accelerated as the IVOL increases.

Original language	English
Journal	Computational Economics
DOIs	https://doi.org/10.1007/s10614-022-10265-3
Publication status	Published - 11 May 2022

Bibliographical note

Publisher Copyright:
© 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Keywords

Idiosyncratic volatility puzzle
Portfolio-based approach
Functional data analysis
China’s A-share markets

ASJC Scopus subject areas

Economics, Econometrics and Finance(all)

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1007/s10614-022-10265-3

Cite this

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title = "Exploring the nonlinear idiosyncratic volatility puzzle: evidence from China",

abstract = "This paper studies the spectrum of the idiosyncratic volatility (IVOL) puzzle in the Chinese A-share market using functional data analysis (FDA). It highlights a nonlinear IVOL puzzle with a steady reduction in the bottom 20% of average returns and a large drop of 1% in the top 10%, consistent with the herding, certainty, and reflection effects in China{\textquoteright}s A-share markets. Furthermore, empirical evidence suggests that the FDA technique has a 30% greater goodness of fit than linear regressions, suggesting that nonlinearity plays a non-negligible role in the IVOL puzzle. These results can be useful for investors and hedgers, as they show that stock returns decline accelerated as the IVOL increases.",

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author = "Sabri Boubaker and Zhenya Liu and Wa{\"e}l Louhichi and Yao Yao",

note = "Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.",

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N2 - This paper studies the spectrum of the idiosyncratic volatility (IVOL) puzzle in the Chinese A-share market using functional data analysis (FDA). It highlights a nonlinear IVOL puzzle with a steady reduction in the bottom 20% of average returns and a large drop of 1% in the top 10%, consistent with the herding, certainty, and reflection effects in China’s A-share markets. Furthermore, empirical evidence suggests that the FDA technique has a 30% greater goodness of fit than linear regressions, suggesting that nonlinearity plays a non-negligible role in the IVOL puzzle. These results can be useful for investors and hedgers, as they show that stock returns decline accelerated as the IVOL increases.

AB - This paper studies the spectrum of the idiosyncratic volatility (IVOL) puzzle in the Chinese A-share market using functional data analysis (FDA). It highlights a nonlinear IVOL puzzle with a steady reduction in the bottom 20% of average returns and a large drop of 1% in the top 10%, consistent with the herding, certainty, and reflection effects in China’s A-share markets. Furthermore, empirical evidence suggests that the FDA technique has a 30% greater goodness of fit than linear regressions, suggesting that nonlinearity plays a non-negligible role in the IVOL puzzle. These results can be useful for investors and hedgers, as they show that stock returns decline accelerated as the IVOL increases.

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Exploring the nonlinear idiosyncratic volatility puzzle: evidence from China

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

UN SDGs

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