Efficient numerical methods for pricing American options

In this thesis we study efficient numerical methods for pricing American options. We apply option pricing models which are based on the Black and Scholes theory and Heston’s stochastic volatility model. Prices for American options are modelled by linear complementarity problems with one-dimensional...

Full description

Bibliographic Details
Main Author: Ikonen, Samuli
Other Authors: University of Jyväskylä, Jyväskylän yliopisto
Format: Doctoral dissertation
Language:eng
Published: 2005
Online Access: https://jyx.jyu.fi/handle/123456789/75819
_version_ 1826225504215105536
author Ikonen, Samuli
author2 University of Jyväskylä Jyväskylän yliopisto
author_facet Ikonen, Samuli University of Jyväskylä Jyväskylän yliopisto Ikonen, Samuli University of Jyväskylä Jyväskylän yliopisto
author_sort Ikonen, Samuli
datasource_str_mv jyx
description In this thesis we study efficient numerical methods for pricing American options. We apply option pricing models which are based on the Black and Scholes theory and Heston’s stochastic volatility model. Prices for American options are modelled by linear complementarity problems with one-dimensional and two-dimensional parabolic partial differential operators. The use of numerical methods is unavoidable because of the complexity of these option pricing problems. Large scale option trading gives a motivation to develop efficient numerical procedures for solving American option pricing problems. In this work we apply a finite difference method to the discretization. After discretization, a sequence of discrete linear complementarity problems should be solved in order to obtain prices for American options. This thesis is built around two types of splitting methods. In the articles of this thesis one is referred as the operator splitting method and the other one as the componentwise splitting method. Operator splitting methods are first applied for solving basic American option pricing models and then they are applied to a solution of a model with a stochastic volatility assumption. The idea in these operator splitting methods is that at each time step a treatment of an obstacle constraint and a solution of a system of linear equations are made in separate fractional steps. Particularly, the advantage of these methods is shown when a stochastic volatility model is used. Componentwise splitting methods are applied for a solution of the American option pricing problem with a stochastic volatility setting and shown to be highly efficient. In a basic form of this splitting a discrete linear complementarity problem is divided in such a way that three linear complementarity problems with tridiagonal matrices need to be solved. The efficiency of this splitting method is based on the use of a direct solver at each fractional step. Strang symmetrization is used to increase the accuracy of this splitting method. The efficiency of the proposed numerical techniques is demonstrated with several numerical experiments. This thesis ends with an article considering a numerical solution of the American option pricing problem with the stochastic volatility assumption where an extensive comparison of efficiency of numerical methods are presented.
first_indexed 2021-05-20T20:00:45Z
format Väitöskirja
free_online_boolean 1
fullrecord [{"key": "dc.contributor.author", "value": "Ikonen, Samuli", "language": null, "element": "contributor", "qualifier": "author", "schema": "dc"}, {"key": "dc.date.accessioned", "value": "2021-05-20T12:42:20Z", "language": null, "element": "date", "qualifier": "accessioned", "schema": "dc"}, {"key": "dc.date.available", "value": "2021-05-20T12:42:20Z", "language": null, "element": "date", "qualifier": "available", "schema": "dc"}, {"key": "dc.date.issued", "value": "2005", "language": null, "element": "date", "qualifier": "issued", "schema": "dc"}, {"key": "dc.identifier.isbn", "value": "978-951-39-8037-5", "language": null, "element": "identifier", "qualifier": "isbn", "schema": "dc"}, {"key": "dc.identifier.uri", "value": "https://jyx.jyu.fi/handle/123456789/75819", "language": null, "element": "identifier", "qualifier": "uri", "schema": "dc"}, {"key": "dc.description.abstract", "value": "In this thesis we study efficient numerical methods for pricing American options. We apply option pricing models which are based on the Black and Scholes theory and Heston\u2019s stochastic volatility model. Prices for American options are modelled by linear complementarity problems with one-dimensional and two-dimensional parabolic partial differential operators. The use of numerical methods is unavoidable because of the complexity of these option pricing problems. Large scale option trading gives a motivation to develop efficient numerical procedures for solving American option pricing problems. In this work we apply a finite difference method to the discretization. After discretization, a sequence of discrete linear complementarity problems should be solved in order to obtain prices for American options. This thesis is built around two types of splitting methods. In the articles of this thesis one is referred as the operator splitting method and the other one as the componentwise splitting method. Operator splitting methods are first applied for solving basic American option pricing models and then they are applied to a solution of a model with a stochastic volatility assumption. The idea in these operator splitting methods is that at each time step a treatment of an obstacle constraint and a solution of a system of linear equations are made in separate fractional steps. Particularly, the advantage of these methods is shown when a stochastic volatility model is used. Componentwise splitting methods are applied for a solution of the American option pricing problem with a stochastic volatility setting and shown to be highly efficient. In a basic form of this splitting a discrete linear complementarity problem is divided in such a way that three linear complementarity problems with tridiagonal matrices need to be solved. The efficiency of this splitting method is based on the use of a direct solver at each fractional step. Strang symmetrization is used to increase the accuracy of this splitting method. The efficiency of the proposed numerical techniques is demonstrated with several numerical experiments. This thesis ends with an article considering a numerical solution of the American option pricing problem with the stochastic volatility assumption where an extensive comparison of efficiency of numerical methods are presented.", "language": "en", "element": "description", "qualifier": "abstract", "schema": "dc"}, {"key": "dc.description.provenance", "value": "Submitted by Harri Hirvi (hirvi@jyu.fi) on 2021-05-20T12:42:20Z\nNo. of bitstreams: 0", "language": "en", "element": "description", "qualifier": "provenance", "schema": "dc"}, {"key": "dc.description.provenance", "value": "Made available in DSpace on 2021-05-20T12:42:20Z (GMT). No. of bitstreams: 0\n Previous issue date: 2005", "language": "en", "element": "description", "qualifier": "provenance", "schema": "dc"}, {"key": "dc.language.iso", "value": "eng", "language": null, "element": "language", "qualifier": "iso", "schema": "dc"}, {"key": "dc.relation.ispartofseries", "value": "Jyv\u00e4skyl\u00e4 studies in computing", "language": null, "element": "relation", "qualifier": "ispartofseries", "schema": "dc"}, {"key": "dc.relation.haspart", "value": "<b>Artikkeli I:</b> Ikonen, S., & Toivanen, J. (2004, 17). Operator splitting methods for American option pricing. <i>Applied Mathematics Letters, (7), 809-814.</i> DOI: <a href=\"https://doi.org/10.1016/j.aml.2004.06.010\"target=\"_blank\">10.1016/j.aml.2004.06.010</a>", "language": "", "element": "relation", "qualifier": "haspart", "schema": "dc"}, {"key": "dc.relation.haspart", "value": "<b>Artikkeli II:</b> Ikonen, S., & Toivanen, J. (2004). Pricing American Options Using LU Decomposition. Reports of the Department of Mathematical Information Technology, 4.", "language": "", "element": "relation", "qualifier": "haspart", "schema": "dc"}, {"key": "dc.relation.haspart", "value": "<b>Artikkeli III:</b> Ikonen, S. & Toivanen, J. (2009). Operator splitting methods for pricing American options under stochastic volatility. <i>Numerische Mathematik, 113, 299\u2013324.</i> DOI: <a href=\"https://doi.org/10.1007/s00211-009-0227-5\"target=\"_blank\"> 10.1007/s00211-009-0227-5</a>", "language": "", "element": "relation", "qualifier": "haspart", "schema": "dc"}, {"key": "dc.relation.haspart", "value": "<b>Artikkeli IV:</b> Ikonen, S., & Toivanen, J. (2007). Componentwise Splitting Methods for Pricing American Options Under Stochastic Volatility. <i>International Journal of Theoretical and Applied Finance, 10(02), 331-361.</i> DOI: <a href=\"https://doi.org/10.1142/S0219024907004202\"target=\"_blank\"> 10.1142/S0219024907004202</a>", "language": "", "element": "relation", "qualifier": "haspart", "schema": "dc"}, {"key": "dc.relation.haspart", "value": "<b>Artikkeli V:</b> Ikonen, S., & Toivanen, J. (2005). Efficient Numerical Methods for Pricing American Options Under Stochastic Volatility. <i>Numerical Methods for Partial Differential Equations, 24(1), 104-126.</i> DOI: <a href=\"https://doi.org/10.1002/num.20239\"target=\"_blank\"> 10.1002/num.20239</a>", "language": "", "element": "relation", "qualifier": "haspart", "schema": "dc"}, {"key": "dc.rights", "value": "In Copyright", "language": null, "element": "rights", "qualifier": null, "schema": "dc"}, {"key": "dc.title", "value": "Efficient numerical methods for pricing American options", "language": null, "element": "title", "qualifier": null, "schema": "dc"}, {"key": "dc.type", "value": "doctoral thesis", "language": null, "element": "type", "qualifier": null, "schema": "dc"}, {"key": "dc.identifier.urn", "value": "URN:ISBN:978-951-39-8037-5", "language": null, "element": "identifier", "qualifier": "urn", "schema": "dc"}, {"key": "dc.contributor.organization", "value": "University of Jyv\u00e4skyl\u00e4", "language": "en", "element": "contributor", "qualifier": "organization", "schema": "dc"}, {"key": "dc.contributor.organization", "value": "Jyv\u00e4skyl\u00e4n yliopisto", "language": "fi", "element": "contributor", "qualifier": "organization", "schema": "dc"}, {"key": "dc.type.coar", "value": "http://purl.org/coar/resource_type/c_db06", "language": null, "element": "type", "qualifier": "coar", "schema": "dc"}, {"key": "dc.rights.accesslevel", "value": "openAccess", "language": null, "element": "rights", "qualifier": "accesslevel", "schema": "dc"}, {"key": "dc.type.publication", "value": "doctoralThesis", "language": null, "element": "type", "qualifier": "publication", "schema": "dc"}, {"key": "dc.rights.url", "value": "https://rightsstatements.org/page/InC/1.0/", "language": null, "element": "rights", "qualifier": "url", "schema": "dc"}, {"key": "dc.date.digitised", "value": "2021", "language": null, "element": "date", "qualifier": "digitised", "schema": "dc"}]
id jyx.123456789_75819
language eng
last_indexed 2025-02-18T10:55:12Z
main_date 2005-01-01T00:00:00Z
main_date_str 2005
online_boolean 1
online_urls_str_mv {"url":"https:\/\/jyx.jyu.fi\/bitstreams\/fd812f8c-fc98-48ab-baf6-2b3381f832c5\/download","text":"Ikonen_Samuli_screen.pdf","source":"jyx","mediaType":"application\/pdf"}
publishDate 2005
record_format qdc
source_str_mv jyx
spellingShingle Ikonen, Samuli Efficient numerical methods for pricing American options
title Efficient numerical methods for pricing American options
title_full Efficient numerical methods for pricing American options
title_fullStr Efficient numerical methods for pricing American options Efficient numerical methods for pricing American options
title_full_unstemmed Efficient numerical methods for pricing American options Efficient numerical methods for pricing American options
title_short Efficient numerical methods for pricing American options
title_sort efficient numerical methods for pricing american options
title_txtP Efficient numerical methods for pricing American options
url https://jyx.jyu.fi/handle/123456789/75819 http://www.urn.fi/URN:ISBN:978-951-39-8037-5
work_keys_str_mv AT ikonensamuli efficientnumericalmethodsforpricingamericanoptions