Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/76570
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dc.contributorSchool of Accounting and Financeen_US
dc.creatorZhong, Xen_US
dc.creatorCao, Jen_US
dc.creatorJin, Yen_US
dc.creatorZheng, Wen_US
dc.date.accessioned2018-05-10T02:56:13Z-
dc.date.available2018-05-10T02:56:13Z-
dc.identifier.issn1465-1211en_US
dc.identifier.urihttp://hdl.handle.net/10397/76570-
dc.language.isoenen_US
dc.publisherIncisive Media Ltd.en_US
dc.rightsCopyright © 2017 Incisive Risk Information (IP) Limiteden_US
dc.rightsThe 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.2017.357en_US
dc.subjectNonparametricen_US
dc.subjectOption pricingen_US
dc.subjectEmpirical likelihooden_US
dc.subjectRobusten_US
dc.subjectBlocking time seriesen_US
dc.titleOn empirical likelihood option pricingen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage41en_US
dc.identifier.epage53en_US
dc.identifier.volume19en_US
dc.identifier.issue5en_US
dc.identifier.doi10.21314/JOR.2017.357en_US
dcterms.abstractThe 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.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationThe journal of risk, June 2017, v. 19, no. 5, p. 41-53en_US
dcterms.isPartOfThe journal of risken_US
dcterms.issued2017-06-
dc.identifier.isiWOS:000402547200003-
dc.identifier.eissn1755-2842en_US
dc.description.validate201805 bcrcen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberAF-0153-
dc.description.fundingSourceRGCen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextThe work described in this paper was partially supported by a grant from the Research Grant Council of the Hong Kong Special Administrative Region, China (Project No. CUHK 458212), the PolyU AF Departmental Research Grant and NSF funding (Project No. DMS- 1612978).en_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS6759863-
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