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Please use this identifier to cite or link to this item: http://repository.li.mahidol.ac.th/dspace/handle/123456789/60449
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dc.contributor.authorNattakorn Phewcheanen_US
dc.contributor.authorRenato Costaen_US
dc.contributor.authorMasnita Misiranen_US
dc.contributor.authorYongwimon Lenburyen_US
dc.contributor.otherMahidol Universityen_US
dc.contributor.otherUniversiti Utara Malaysiaen_US
dc.contributor.otherPERDOen_US
dc.date.accessioned2020-12-28T04:58:01Z-
dc.date.available2020-12-28T04:58:01Z-
dc.date.issued2020-01-01en_US
dc.identifier.citationInternational Journal of Circuits, Systems and Signal Processing. Vol.14, (2020), 821-825en_US
dc.identifier.issn19984464en_US
dc.identifier.other2-s2.0-85097209741en_US
dc.identifier.urihttp://repository.li.mahidol.ac.th/dspace/handle/123456789/60449-
dc.description.abstract© 2020, North Atlantic University Union NAUN. All rights reserved. We investigate the derivation of option pricing involving several assets following the Geometric Brownian Motion (GBM). First, we propose some derivations based on the basic ideas of the assets. Next, we consider the trivial case where we have n assets. Finally, we consider different drifts, volatilities and Wiener processes but now from n stochastic assets taking into account a fixed-income.en_US
dc.rightsMahidol Universityen_US
dc.source.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85097209741&origin=inwarden_US
dc.subjectComputer Scienceen_US
dc.subjectEngineeringen_US
dc.titleAlternative methods to derive the black-scholes-merton equationen_US
dc.typeArticleen_US
dc.rights.holderSCOPUSen_US
dc.identifier.doi10.46300/9106.2020.14.106en_US
dc.identifier.urlhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85097209741&origin=inwarden_US
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