Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12188/23120
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dc.contributor.authorBasnarkov, Laskoen_US
dc.contributor.authorStojkoski, Viktoren_US
dc.contributor.authorUtkovski, Zoranen_US
dc.contributor.authorKocarev, Ljupchoen_US
dc.date.accessioned2022-09-27T08:36:04Z-
dc.date.available2022-09-27T08:36:04Z-
dc.date.issued2019-11-03-
dc.identifier.urihttp://hdl.handle.net/20.500.12188/23120-
dc.description.abstractA growing body of literature suggests that heavy tailed distributions represent an adequate model for the observations of log returns of stocks. Motivated by these findings, here we develop a discrete time framework for pricing of European options. Probability density functions of log returns for different periods are conveniently taken to be convolutions of the Student’s t-distribution with three degrees of freedom. The supports of these distributions are truncated in order to obtain finite values for the options. Within this framework, options with different strikes and maturities for one stock rely on a single parameter – the standard deviation of the Student’s t-distribution for unit period. We provide a study which shows that the distribution support width has weak influence on the option prices for certain range of values of the width. It is furthermore shown that such family of truncated distributions approximately satisfies the no-arbitrage principle and the put-call parity. The relevance of the pricing procedure is empirically verified by obtaining remarkably good match of the numerically computed values by our scheme to real market data.en_US
dc.publisherWorld Scientific Publishing Companyen_US
dc.relation.ispartofInternational Journal of Theoretical and Applied Financeen_US
dc.subjectAsset pricing; Option pricing; Heavy-tailed distributions; Truncated distributionsen_US
dc.titleOption pricing with heavy-tailed distributions of logarithmic returnsen_US
dc.typeJournal Articleen_US
item.grantfulltextopen-
item.fulltextWith Fulltext-
crisitem.author.deptFaculty of Computer Science and Engineering-
Appears in Collections:Faculty of Computer Science and Engineering: Journal Articles
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