Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/76570
Title: On empirical likelihood option pricing
Authors: Zhong, XL
Cao, J
Jin, Y 
Zheng, AW
Keywords: Nonparametric
Option pricing
Empirical likelihood
Robust
Blocking time series
Issue Date: 2017
Publisher: Incisive Media Ltd.
Source: The journal of risk, 2017, v. 19, no. 5, p. 41-53 How to cite?
Journal: The journal of risk 
Abstract: 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.
URI: http://hdl.handle.net/10397/76570
ISSN: 1465-1211
EISSN: 1755-2842
DOI: 10.21314/JOR.2017.357
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