Forecasting VIX using filtered historical simulation
Jiang, Y. and Lazar, E.
It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing. To link to this item DOI: 10.1093/jjfinec/nbaa041 Abstract/SummaryWe propose a new VIX forecast method using GARCH models based on the filtered historical simulation put forward in Barone-Adesi et al. (2008). The flexible change of measure accommodates for non-normalities such as negative skewness and positive excess kurtosis. We present an application for four well-established volatility indices (VIX9D, VIX, VIX3M and VIX6M). Our results show that our proposed estimation method outperforms the Normal-VIX model of Hao and Zhang (2013) both in-sample and out-of-sample. Furthermore, the use of volatility indices reduces the computational burden significantly compared to the options based pricing method.
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