Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/76570
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Title: On empirical likelihood option pricing
Authors: Zhong, X
Cao, J
Jin, Y 
Zheng, W
Issue Date: Jun-2017
Source: The journal of risk, June 2017, v. 19, no. 5, p. 41-53
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.
Keywords: Nonparametric
Option pricing
Empirical likelihood
Robust
Blocking time series
Publisher: Incisive Media Ltd.
Journal: The journal of risk 
ISSN: 1465-1211
EISSN: 1755-2842
DOI: 10.21314/JOR.2017.357
Rights: Copyright © 2017 Incisive Risk Information (IP) Limited
The following publication Zhong, X., Cao, J., Jin, Y., & Zheng, W. (2017). On empirical likelihood option pricing. Journal of Risk, 19(5), 41-53 is available at https://doi.org/10.21314/JOR.2017.357
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