Option pricing with simulation of fuzzy stochastic variables

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dc.contributor.authorHolčapek, Michal
dc.contributor.authorTichý, Tomáš
dc.contributor.otherEkonomická fakultacs
dc.date.accessioned2014-05-22
dc.date.available2014-05-22
dc.date.issued2013-08
dc.description.abstractDuring last decades the stochastic simulation approach, both via MC and QMC has been vastly applied and subsequently analyzed in almost all branches of science. Very nice applications can be found in areas that rely on modeling via stochastic processes, such as finance. However, since financial quantities as opposed to natural processes depend on human activity, their modeling is often very challenging. Many scholars therefor suggest to specify some parts of financial models by means of fuzzy set theory. Many financial problems, such as pricing and hedging of specific financial derivatives, are too complex to be solved analytically even in a crisp case, it can be efficient to apply (Quasi) Monte Carlo simulation. In this contribution a recent knowledge of fuzzy numbers and their approximation is utilized in order to suggest fuzzy-MC simulation to option price modeling in terms of fuzzy-random variables. In particular, we suggest three distinct fuzzy-random processes as an alternative to a standard crisp model. Application possibilities are shown on illustrative examples assuming a plain vanilla European put option under Brownian motion with fuzzy parameter (volatility), Brownian motion with fuzzy subordinator and Brownian motion with fuzzyfied subordinator. In each case the model result into a whole set of prices – thus, since we assume one of the input data as LU fuzzy number, we get the price in terms of the LU fuzzy number as well. The payoff function of analyzed put option can be obviously replaced by more complex payoff structure.en
dc.formattext
dc.format.extent201-211cs
dc.identifier.isbn978-80-7372-953-0
dc.identifier.urihttps://dspace.tul.cz/handle/15240/6915
dc.language.isoen
dc.publisherTechnická Univerzita v Libercics
dc.publisherTechnical university of Liberec, Czech Republicen
dc.publisher.abbreviationTUL
dc.relation.ispartofseriesLiberec economic forum 2013: proceedings of the 11th international conference: 16th - 17th September 2013, Sychrov, Czech republic, EU /[editor Aleš Kocourek];1
dc.subjectrandom variableen
dc.subjectfuzzy variableen
dc.subjectoptionen
dc.subjectsimulationen
dc.subject.classificationC46
dc.subject.classificationE37
dc.subject.classificationG17
dc.subject.classificationG24
dc.titleOption pricing with simulation of fuzzy stochastic variablescs
dc.typeArticleen
local.accessopen
local.facultyFaculty of Economics
local.fulltextyes
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