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Pricing American options using a space-time adaptive finite difference method
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis. (ndim)
Responsible organisation
2007 (English)Report (Other academic)
Abstract [en]

American options are priced numerically using a space- and time-adaptive finite difference method. The generalized Black-Scholes operator is discretized on a Cartesian structured but non-equidistant grid in space. The space- and time-discretizations are adjusted such that a predefined tolerance level on the local discretization error is met. An operator splitting technique is used to separately handle the early exercise constraint and the solution of linear systems of equations from the finite difference discretization of the linear complementarity problem. In numerical experiments three variants of the adaptive time-stepping algorithm with and without local time-stepping are compared.

Place, publisher, year, edition, pages
2007.
Series
Technical report / Department of Information Technology, Uppsala University, ISSN 1404-3203 ; 2007-004
National Category
Computational Mathematics Computer Sciences
Identifiers
URN: urn:nbn:se:uu:diva-23576OAI: oai:DiVA.org:uu-23576DiVA, id: diva2:51350
Available from: 2007-02-01 Created: 2009-01-28 Last updated: 2024-05-30Bibliographically approved
In thesis
1. Accurate Finite Difference Methods for Option Pricing
Open this publication in new window or tab >>Accurate Finite Difference Methods for Option Pricing
2006 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Stock options are priced numerically using space- and time-adaptive finite difference methods. European options on one and several underlying assets are considered. These are priced with adaptive numerical algorithms including a second order method and a more accurate method. For American options we use the adaptive technique to price options on one stock with and without stochastic volatility. In all these methods emphasis is put on the control of errors to fulfill predefined tolerance levels. The adaptive second order method is compared to an alternative discretization technique using radial basis functions. This method is not adaptive but shows potential in option pricing for one and several underlying assets. A finite difference method and a Monte Carlo method are applied to a new financial contract called Turbo warrant. A comparison of these two methods shows that for the case considered the finite difference method is superior.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2006. p. 70
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 206
Keywords
Finite differences, Option pricing, Adaptive methods
National Category
Computational Mathematics
Research subject
Numerical Analysis
Identifiers
urn:nbn:se:uu:diva-7097 (URN)91-554-6627-3 (ISBN)
Public defence
2006-09-29, Room 2446, Polacksbacken, Lägerhyddsvägen 2D, Uppsala, 10:15 (English)
Opponent
Supervisors
Available from: 2006-09-08 Created: 2006-09-08 Last updated: 2011-10-27Bibliographically approved

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Persson, Jonas

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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