Conditional Heteroskedasticity in the Volatility of Asset Returns

Yashuang (Dexter) Ding

Cambridge Working Papers in Economics from Faculty of Economics, University of Cambridge

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 (search for similar items in EconPapers)
JEL-codes: C22 C32 C53 C58 G17 (search for similar items in EconPapers)
Date: 2021-11-09
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-ore
Note: yd274
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Persistent link: https://EconPapers.repec.org/RePEc:cam:camdae:2179

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