Numerical studies on approximate option prices
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Yoon, Jeongyoen | - |
dc.contributor.author | Seung, Jisu | - |
dc.contributor.author | Song, Seongjoo | - |
dc.date.accessioned | 2021-09-03T07:45:28Z | - |
dc.date.available | 2021-09-03T07:45:28Z | - |
dc.date.created | 2021-06-16 | - |
dc.date.issued | 2017-04 | - |
dc.identifier.issn | 1225-066X | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/83947 | - |
dc.description.abstract | In this paper, we compare several methods to approximate option prices: Edgeworth expansion, A-type and C-type Gram-Charlier expansions, a method using normal inverse gaussian (NIG) distribution, and an asymptotic method using nonlinear regression. We used two different types of approximation. The first (called the RNM method) approximates the risk neutral probability density function of the log return of the underlying asset and computes the option price. The second (called the OPTIM method) finds the approximate option pricing formula and then estimates parameters to compute the option price. For simulation experiments, we generated underlying asset data from the Heston model and NIG model, a well-known stochastic volatility model and a well-known Levy model, respectively. We also applied the above approximating methods to the KOSPI200 call option price as a real data application. We then found that the OPTIM method shows better performance on average than the RNM method. Among the OPTIM, A type Gram-Charlier expansion and the asymptotic method that uses nonlinear regression showed relatively better performance; in addition, among RNM, the method of using NIG distribution was relatively better than others. | - |
dc.language | Korean | - |
dc.language.iso | ko | - |
dc.publisher | KOREAN STATISTICAL SOC | - |
dc.subject | JUMP LEVY PROCESSES | - |
dc.subject | RETURNS | - |
dc.title | Numerical studies on approximate option prices | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Song, Seongjoo | - |
dc.identifier.doi | 10.5351/KJAS.2017.30.2.243 | - |
dc.identifier.wosid | 000424584900004 | - |
dc.identifier.bibliographicCitation | KOREAN JOURNAL OF APPLIED STATISTICS, v.30, no.2, pp.243 - 257 | - |
dc.relation.isPartOf | KOREAN JOURNAL OF APPLIED STATISTICS | - |
dc.citation.title | KOREAN JOURNAL OF APPLIED STATISTICS | - |
dc.citation.volume | 30 | - |
dc.citation.number | 2 | - |
dc.citation.startPage | 243 | - |
dc.citation.endPage | 257 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.identifier.kciid | ART002221264 | - |
dc.description.journalClass | 2 | - |
dc.description.journalRegisteredClass | kci | - |
dc.relation.journalResearchArea | Mathematics | - |
dc.relation.journalWebOfScienceCategory | Statistics & Probability | - |
dc.subject.keywordPlus | JUMP LEVY PROCESSES | - |
dc.subject.keywordPlus | RETURNS | - |
dc.subject.keywordAuthor | asymptotic option price | - |
dc.subject.keywordAuthor | Gram-Charlier expansion | - |
dc.subject.keywordAuthor | Heston model | - |
dc.subject.keywordAuthor | normal inverse gaussian process | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
145 Anam-ro, Seongbuk-gu, Seoul, 02841, Korea+82-2-3290-2963
COPYRIGHT © 2021 Korea University. All Rights Reserved.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.