• Home
  • Library
  • Theses
  • AN EFFICIENT OPERATOR SPLITTING TECHNIQUE FOR OPTION PRICING UNDER STOCHASTIC VOLATILITY
 

Publication:
AN EFFICIENT OPERATOR SPLITTING TECHNIQUE FOR OPTION PRICING UNDER STOCHASTIC VOLATILITY

Simple item page
datacite.subject.fosNatural sciences
dc.contributor.authorChidzalo, Patrick
dc.date.accessioned2025-01-13T11:29:43Z
dc.date.available2025-01-13T11:29:43Z
dc.date.issued2018-01-01
dc.descriptionThesis submitted to the Department of Mathematical Sciences, Faculty of Science,in partial fulfillment of the requirements for the degree of Master of Science (Mathematical Sciences)
dc.description.abstractStochastic Volatility models are more realistic than the Black-Scholes model for Vanilla option pricing, because risk neutrality assumption is avoided. We solve He ston’s stochastic volatility model, that has been solved using Monte-Carlo method which is computationally realistic in the third dimension only; and Finite difference methods that are more efficient, but face curse of dimensionality in at least three dimensions. This study adopts the Strang’s operator splitting method that uses stochastically weighted sub-problems. Fourth order Runge-Kutta method for partial differential equations are used within finite difference formulations of the split sub-problems. Charpit method is applied in the nonlinear part of the Option pricing model. The method has second order truncation error and is computationally more realistic, which is verified by the Chicago Board of Options Exchange data. The running time of computer powered simulations are lower than those found in the two methods.
dc.identifier.urihttps://dspace.unima.ac.mw/handle/123456789/529
dc.language.isoen
dc.schoolscentersoptionsb0e8094e-c230-4f28-8ae9-b0fc60729932
dc.subjectStochastic Volatility
dc.subjectVanilla
dc.subjectBlack-scholes
dc.subjectRisk neutrality
dc.subjectPrice
dc.subjectBlack-Scholes model
dc.subjectComputer powered simulations
dc.subjectOption pricing model
dc.subjectRisk neutrality assumption
dc.supervisorc51bd14a-3f0b-4050-9b92-3af875da5efc
dc.titleAN EFFICIENT OPERATOR SPLITTING TECHNIQUE FOR OPTION PRICING UNDER STOCHASTIC VOLATILITY
dc.typetext::thesis::master thesis
dspace.entity.typePublication
oairecerif.author.affiliationUniversity of Malawi

Files

Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
Chidzalo P. 2018.pdf
Size:
1.98 MB
Format:
Adobe Portable Document Format
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed to upon submission
Description:
Download

Collections

Theses