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Forecasting VIX using two-component realized EGARCH model

delete2023-07-01
delete6
PRE
AI
X
Xinyu Wu
A
An Zhao
L
Li Liu *
DOI:10.1016/j.najef.2023.101934delete
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摘要

摘要

En 中文
In this paper, we propose the two-component realized EGARCH (REGARCH-2C) model, which accommodates the high-frequency information and the long memory volatility through the realized measure of volatility and the component volatility structure, to forecast VIX. We obtain the risk-neutral dynamics of the REGARCH-2C model and derive the corresponding model-implied VIX formula. The parameter estimates of the REGARCH-2C model are obtained via the joint maximum likelihood estimation using observations on the returns, realized measure and VIX. Our empirical results demonstrate that the proposed REGARCH-2C model provides more accurate VIX forecasts compared to a variety of competing models, including the GARCH, GJR-GARCH, nonlinear GARCH, Heston-Nandi GARCH, EGARCH, REGARCH and two two-component GARCH models. This result is found to be robust to alternative realized measure. Our empirical evidence highlights the importance of incorporating the realized measure as well as the component volatility structure for VIX forecasting.
Keyword:
VIX forecasting
Realized EGARCH
Component volatility structure
Realized measure

期刊

North American Journal of Economics and Finance 封面图
North American Journal of Economics and Finance
IF:
3.9
论文数:
2.0K
被引数:
4.8K

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