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dc.contributor.advisorMcCrorie, Roderick
dc.contributor.authorCao, Liang
dc.coverage.spatial345en_US
dc.date.accessioned2015-04-22T15:19:10Z
dc.date.available2015-04-22T15:19:10Z
dc.date.issued2014-12-01
dc.identifieruk.bl.ethos.644829
dc.identifier.urihttps://hdl.handle.net/10023/6539
dc.description.abstractThis thesis considers new methods that exploit recent developments in computer technology to address three extant problems in the area of Finance and Econometrics. The problem of Asian option pricing has endured for the last two decades in spite of many attempts to find a robust solution across all parameter values. All recently proposed methods are shown to fail when computations are conducted using standard machine precision because as more and more accuracy is forced upon the problem, round-off error begins to propagate. Using recent methods from numerical analysis based on multi-precision arithmetic, we show using the Mathematica platform that all extant methods have efficacy when computations use sufficient arithmetic precision. This creates the proper framework to compare and contrast the methods based on criteria such as computational speed for a given accuracy. Numerical methods based on a deformation of the Bromwich contour in the Geman-Yor Laplace transform are found to perform best provided the normalized strike price is above a given threshold; otherwise methods based on Euler approximation are preferred. The same methods are applied in two other contexts: the simulation of stable distributions and the computation of unit root densities in Econometrics. The stable densities are all nested in a general function called a Fox H function. The same computational difficulties as above apply when using only double-precision arithmetic but are again solved using higher arithmetic precision. We also consider simulating the densities of infinitely divisible distributions associated with hyperbolic functions. Finally, our methods are applied to unit root densities. Focusing on the two fundamental densities, we show our methods perform favorably against the extant methods of Monte Carlo simulation, the Imhof algorithm and some analytical expressions derived principally by Abadir. Using Mathematica, the main two-dimensional Laplace transform in this context is reduced to a one-dimensional problem.en_US
dc.language.isoenen_US
dc.publisherUniversity of St Andrews
dc.rightsCreative Commons Attribution 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectLaplace transformsen_US
dc.subjectNumerical inversionen_US
dc.subjectMulti-precision arithmeticen_US
dc.subjectAsian optionsen_US
dc.subjectInfinitely divisible distributionsen_US
dc.subjectStable distributionsen_US
dc.subjectUnit root distributionsen_US
dc.subjectCharacteristic functionsen_US
dc.subjectGeneralized hypergeometric functionen_US
dc.subjectMeijer G functionen_US
dc.subjectFox H functionen_US
dc.subjectEuler methoden_US
dc.subjectPost-Widder methoden_US
dc.subjectBromwich integralen_US
dc.subjectGaver-Wynn-Rho algorithmen_US
dc.subjectFixed Talbot methoden_US
dc.subjectUnified Gaver-Stehfest algorithmen_US
dc.subjectUnified Euler algorithmen_US
dc.subjectUnified Talbot algorithmen_US
dc.subjectLaguerre methoden_US
dc.subjectSpectral series expansionen_US
dc.subjectConstructive complex analysisen_US
dc.subjectAsymptotic methoden_US
dc.subjectPDE methoden_US
dc.subjectMonte Carlo simulationen_US
dc.subjectTurnbull and Wakeman approximationen_US
dc.subjectMilevsky and Posner approximationen_US
dc.subjectJoint densitiesen_US
dc.subjectJoint distribution functionsen_US
dc.subjectTransformation of joint densityen_US
dc.subjectMathematicaen_US
dc.subject.lccHG6024.A7C2
dc.subject.lcshOptions (Finance)--Prices--Asia--Mathematical modelsen_US
dc.subject.lcshNumerical analysis--Data processingen_US
dc.subject.lcshRoundoff errorsen_US
dc.titleNumerical analysis and multi-precision computational methods applied to the extant problems of Asian option pricing and simulating stable distributions and unit root densitiesen_US
dc.typeThesisen_US
dc.type.qualificationlevelDoctoralen_US
dc.type.qualificationnamePhD Doctor of Philosophyen_US
dc.publisher.institutionThe University of St Andrewsen_US


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Creative Commons Attribution 4.0 International
Except where otherwise noted within the work, this item's licence for re-use is described as Creative Commons Attribution 4.0 International