Conditional Heteroskedasticity in the Volatility of Asset Returns
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Authors
Ding, Y.
Publication Date
2021-11-08Series
Cambridge Working Papers in Economics
Publisher
Faculty of Economics, University of Cambridge
Type
Working Paper
Metadata
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Ding, Y. (2021). Conditional Heteroskedasticity in the Volatility of Asset Returns. https://doi.org/10.17863/CAM.79371
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
GARCH, SHARV, volatility, volatility of volatility, forecasting
Identifiers
CWPE2179, JIWP2111
This record's DOI: https://doi.org/10.17863/CAM.79371
This record's URL: https://www.repository.cam.ac.uk/handle/1810/331922
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