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 | |
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)