Ding, Y.
Conditional Heteroskedasticity in the Volatility of Asset Returns
JIWP Number: 2111
Abstract: We propose a new class of conditional heteroskedasticity in the volatility (CHV) models which allows for time-varying volatility of volatility in the volatility of asset returns. This class nests a variety of GARCH-type models and the SHARV model of Ding (2021). CH-V models can be seen as a special case of the stochastic volatility of volatility model. We then introduce two examples of CH-V in which we specify a GJR-GARCH and an E-GARCH processes for the volatility of volatility, respectively. We also show a novel way of introducing the leverage effect of negative returns on the volatility through the volatility of volatility process. Empirical study confirms that CH-V models have better goodness-of-fit and out-of-sample volatility and Value-at-Risk forecasts than common GARCH-type models.
Keywords: forecasting, GARCH, SHARV, volatility, volatility of volatility
JEL Codes: C22 C32 C53 C58 G17
Author links:
PDF: jiwp2111.pdf 
Open Access Link: 10.17863/CAM.79371
