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dc.date.accessioned2013-03-12T08:19:31Z
dc.date.available2013-03-12T08:19:31Z
dc.date.issued2005en_US
dc.date.submitted2009-11-24en_US
dc.identifier.urihttp://hdl.handle.net/10852/10568
dc.description.abstractWe propose a quasi-Monte Carlo (qMC) algorithm to simulate variates from the normal inverse Gaussian (NIG) distribution. The algorithm is based on a Monte Carlo technique found in the Rydberg reference, and is based on sampling three independent uniform variables. We apply the algorithm to three problems appearing in finance. First, we consider the valuation of plain vanilla call options and Asian options. The next application considers the problem of deriving implied parameters for the underlying asset dynamics based on observed option prices. We employ our proposed algorithm together with the Newton Method, and show how we can find the scale parameter of the NIG-distribution of the logreturns in case of a call or an Asian option. We also provide an extensive error analysis for this method. Finally we study the calculation of Value-at-Risk for a portfolio of nonlinear products where the returns are modeled by NIG random variables.eng
dc.language.isoengen_US
dc.publisherMatematisk Institutt, Universitetet i Oslo
dc.relation.ispartofPreprint series. Pure mathematics http://urn.nb.no/URN:NBN:no-8076en_US
dc.relation.urihttp://urn.nb.no/URN:NBN:no-8076
dc.titleA QUASI-MONTE CARLO ALGORITHM FOR THE NORMAL INVERSE GAUSSIAN DISTRIBUTION AND VALUATION OF FINANCIAL DERIVATIVESen_US
dc.typeResearch reporten_US
dc.date.updated2009-11-24en_US
dc.creator.authorBenth, Fred Espenen_US
dc.creator.authorGroth, Martinen_US
dc.creator.authorKettler, Paul C.en_US
dc.subject.nsiVDP::410en_US
dc.identifier.urnURN:NBN:no-23602en_US
dc.type.documentForskningsrapporten_US
dc.identifier.duo97211en_US
dc.identifier.fulltextFulltext https://www.duo.uio.no/bitstream/handle/10852/10568/1/pm14-05.pdf


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