Exploring the Nonlinear Idiosyncratic Volatility Puzzle: Evidence from China

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.