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Optimization of American option pricing though GPU computing
KTH, School of Computer Science and Communication (CSC).
KTH, School of Computer Science and Communication (CSC).
2017 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesisAlternative title
Optimering av prissättning av amerikanska optioner genom GPU-beräkningar (Swedish)
Abstract [en]

Over the last decades the market for financial derivatives has grown dramatically to values of global importance. With the digital automation of the markets, programs able to efficiently value financial derivatives has become key to market competitiveness and thus garnered considerable interest. This report explores the potential efficiency gains of employing modern technology in GPU computing to price financial options, using the binomial option pricing model. The model is implemented using both CPU and GPU hardware and results compared in terms of computational efficiency. According to this thesis, GPU computing can considerably improve option pricing runtimes.

Abstract [sv]

Under de senaste decennierna har marknaden för finansiella derivatinstrument vuxit till värden av global betydelse. Med ökande digitalisering av marknaden har program som effektivt kan värdera derivatinstrument blivit avgörande för konkurrenskraft och därför givits avsevärt intresse. Denna rapport utforskar vilka möjliga ökningar i effektivitet som kan nås genom att använda modern teknik för GPU-beräkningar för att värdera finansiella optioner genom den binomiala optionsvärderingsmodellen. Modellen implementeras både med CPU-, och GPU-hårdvara och resultaten jämförs i termer av beräkningseffektivitet. Enligt denna studie kan GPU-beräkingar avsevärt förbättra körtider för optionsvärderingar.

Place, publisher, year, edition, pages
2017. , p. 26
Keywords [en]
finance, options, GPU, GPGPU, GPU computing, binomial method, BOPM, CUDA
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:kth:diva-208377OAI: oai:DiVA.org:kth-208377DiVA, id: diva2:1105924
Supervisors
Examiners
Available from: 2017-06-19 Created: 2017-06-05 Last updated: 2018-01-13Bibliographically approved

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thesis(619 kB)193 downloads
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Type fulltextMimetype application/pdf

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Greinsmark, HadarLindström, Erik
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CiteExportLink to record
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Citation style
  • apa
  • ieee
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  • vancouver
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  • en-US
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  • nn-NB
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  • Other locale
More languages
Output format
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