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Option pricing under the double exponential jump-diffusion model by using the Laplace transform: Application to the Nordic market
Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE). (Finance Mathematics)
Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE). (Finance Mathematics)
2010 (English)Independent thesis Advanced level (degree of Master (One Year)), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

In this thesis the double exponential jump-diffusion model is considered and the Laplace transform is used as a method for pricing both plain vanilla and path-dependent options. The evolution of the underlying stock prices are assumed to follow a double exponential jump-diffusion model. To invert the Laplace transform, the Euler algorithm is used. The thesis includes the programme code for European options and the application to the real data. The results show how the Kou model performs on the NASDAQ OMX Stockholm Market in the case of the SEB stock.

Place, publisher, year, edition, pages
2010. , 71 p.
Keyword [en]
Financial Mathematics, Laplace transform, Kou model, Double Exponential Jump-Diffusion, option pricing
National Category
Mathematics Other Mathematics Computational Mathematics
Identifiers
URN: urn:nbn:se:hh:diva-5336OAI: oai:DiVA.org:hh-5336DiVA: diva2:343268
Presentation
Haldasalen, Halmstad University, 301 18, Halmstad, Halmstad, Sweden (English)
Uppsok
Physics, Chemistry, Mathematics
Supervisors
Examiners
Available from: 2010-08-13 Created: 2010-08-12 Last updated: 2010-08-13Bibliographically approved

Open Access in DiVA

fulltext(762 kB)1048 downloads
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Type fulltextMimetype application/pdf

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf