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Pricing VIX options with volatility clustering
Author(s) -
Jing Bo,
Li Shenghong,
Ma Yong
Publication year - 2020
Publication title -
journal of futures markets
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.88
H-Index - 55
eISSN - 1096-9934
pISSN - 0270-7314
DOI - 10.1002/fut.22092
Subject(s) - volatility clustering , volatility (finance) , cluster analysis , econometrics , economics , valuation (finance) , valuation of options , implied volatility , volatility smile , financial economics , computer science , finance , autoregressive conditional heteroskedasticity , artificial intelligence
We investigate the valuation of volatility index (VIX) options by developing a model with a self‐exciting Hawkes process that allows for clustering in the VIX. In the proposed framework, we find semianalytical expressions for the characteristic function and forward characteristic function, and then we solve the pricing problem of standard‐start and forward‐start options via the fast Fourier transform. The empirical results provide evidence to support the significance of accounting for volatility clustering when pricing VIX options.