{"title":"Efficient Variations of the Fourier Transform in Applications to Option Pricing","authors":"S. Boyarchenko, S. Levendorskii","doi":"10.21314/JCF.2014.277","DOIUrl":null,"url":null,"abstract":"In this paper, we clarify the relationships among popular methods for pricing European options based on the Fourier expansion of the payoff function (iFT method) and the simlified trapezoid rule. We suggest new variations that allow us to decrease the number of terms by a factor of between five and ten (when the iFT requires several dozen terms), or even by a factor of several dozen or a hundred (when the iFT may need thousands or millions of terms). We also give efficient recommendations for an (approximately) optimal choice of parameters for each numerical scheme.","PeriodicalId":51731,"journal":{"name":"Journal of Computational Finance","volume":"1 1","pages":""},"PeriodicalIF":0.8000,"publicationDate":"2014-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"39","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computational Finance","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.21314/JCF.2014.277","RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
引用次数: 39
Abstract
In this paper, we clarify the relationships among popular methods for pricing European options based on the Fourier expansion of the payoff function (iFT method) and the simlified trapezoid rule. We suggest new variations that allow us to decrease the number of terms by a factor of between five and ten (when the iFT requires several dozen terms), or even by a factor of several dozen or a hundred (when the iFT may need thousands or millions of terms). We also give efficient recommendations for an (approximately) optimal choice of parameters for each numerical scheme.
期刊介绍：
The Journal of Computational Finance is an international peer-reviewed journal dedicated to advancing knowledge in the area of financial mathematics. The journal is focused on the measurement, management and analysis of financial risk, and provides detailed insight into numerical and computational techniques in the pricing, hedging and risk management of financial instruments. The journal welcomes papers dealing with innovative computational techniques in the following areas: Numerical solutions of pricing equations: finite differences, finite elements, and spectral techniques in one and multiple dimensions. Simulation approaches in pricing and risk management: advances in Monte Carlo and quasi-Monte Carlo methodologies; new strategies for market factors simulation. Optimization techniques in hedging and risk management. Fundamental numerical analysis relevant to finance: effect of boundary treatments on accuracy; new discretization of time-series analysis. Developments in free-boundary problems in finance: alternative ways and numerical implications in American option pricing.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
