Journal of Risk

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On empirical likelihood option pricing

Xiaolong Zhong, Jie Cao, Yong Jin and Wei Zheng

  • Proposed an empirical likelihood based option pricing method.
  • New method performs reasonably well especially when accounting for jumps and stochastic volatility.
  • The nonparametric methods capture information about higher order moments.
     

The Black–Scholes model is the golden standard for pricing derivatives and options in the modern financial industry. However, this method imposes some parametric assumptions on the stochastic process, and its performance becomes doubtful when these assumptions are violated. This paper investigates the application of a nonparametric method, namely the empirical likelihood (EL) method, in the study of option pricing. A blockwise EL procedure is proposed to deal with dependence in the data. Simulation and real data studies show that this new method performs reasonably well and, more importantly, outperforms classical models developed to account for jumps and stochastic volatility, thanks to the fact that nonparametric methods capture information about higher-order moments.

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