On empirical likelihood option pricing

Xiaolong Zhong, Jie Cao, Yong Jin, Wei Zheng

Research output: Journal article publicationJournal articleAcademic researchpeer-review

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.
Original languageEnglish
Pages (from-to)41-53
Number of pages13
JournalJournal of Risk
Volume19
Issue number5
DOIs
Publication statusPublished - 1 Jun 2017

Keywords

  • Blocking time series
  • Empirical likelihood
  • Nonparametric
  • Option pricing
  • Robust

ASJC Scopus subject areas

  • Strategy and Management
  • Finance

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