Pricing 50ETF Options Considering Jump Volatility and Signed Jumps

Abstract

Abstract:

The volatility of the underlying asset is key for option pricing. We use high-frequency prices to calculate realized volatility and separate it into jump and continuous volatilities. Heterogeneous autoregressive gamma with parabolic leverages model is constructed for the continuous volatility, which is then augmented by including the signed jumps. Compound Poisson process is used to model the jump volatility, with the random jump sizes Gamma distributed. The parameter estimates are mapped from physical measure to risk-neutral measure, which are then used in the Monte Carlo simulations for option pricing. Experiments with the 50ETF option data from February 9, 2015 to June 30, 2017 show that, under the option price root mean square error and the implied volatility root mean square error, the high-frequency based models all have better option pricing performance than the GARCH model, modeling the jump volatility can improve option pricing, and the best option pricing performance is obtained by further including the singed jumps.

Key words: option pricing, high-frequency data, jump volatility, signed jump, Monte Carlo simulation

Qu Hui, Chen Jingwen. Pricing 50ETF Options Considering Jump Volatility and Signed Jumps[J]. , 2019, 31(9): 28-36.

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