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An alternative model for multivariate stable distributions

Includes bibliographical references (leaves 52-55).

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Bibliographic Details
Main Author: Jama, Siphamandla
Other Authors: Guo, Renkuan
Format: Thesis
Language:English
Published: Department of Statistical Sciences 2014
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access_status_str Open Access
author Jama, Siphamandla
author2 Guo, Renkuan
author_browse Guo, Renkuan
Jama, Siphamandla
author_facet Guo, Renkuan
Jama, Siphamandla
author_sort Jama, Siphamandla
collection Thesis
description Includes bibliographical references (leaves 52-55).
format Thesis
id oai:open.uct.ac.za:11427/8959
institution University of Cape Town (South Africa)
language eng
last_indexed 2026-06-10T12:48:51.997Z
license_str Not specified — see source repository
provenance_str_mv Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository
publishDate 2014
publishDateRange 2014
publishDateSort 2014
publisher Department of Statistical Sciences
publisherStr Department of Statistical Sciences
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source_str UCTD — University of Cape Town Open Access Repository
spelling oai:open.uct.ac.za:11427/8959 An alternative model for multivariate stable distributions Jama, Siphamandla Guo, Renkuan Financial Mathematics Includes bibliographical references (leaves 52-55). As the title, "An Alternative Model for Multivariate Stable Distributions", depicts, this thesis draws from the methodology of [J36] and derives an alternative to the sub-Gaussian alpha-stable distribution as another model for multivariate stable data without using the spectral measure as a dependence structure. From our investigation, firstly, we echo that the assumption of "Gaussianity" must be rejected, as a model for, particularly, high frequency financial data based on evidence from the Johannesburg Stock Exchange (JSE). Secondly, the introduced technique adequately models bivariate return data far better than the Gaussian model. We argue that unlike the sub-Gaussian stable and the model involving a spectral measure this technique is not subject to estimation of a joint index of stability, as such it may remain a superior alternative in empirical stable distribution theory. Thirdly, we confirm that the Gaussian Value-at-Risk and Conditional Value-at-Risk measures are more optimistic and misleading while their stable counterparts are more informative and reasonable. Fourthly, our results confirm that stable distributions are more appropriate for portfolio optimization than the Gaussian framework. 2014-10-30T13:49:35Z 2014-10-30T13:49:35Z 2009 Master Thesis Masters MSc http://hdl.handle.net/11427/8959 eng application/pdf Department of Statistical Sciences Faculty of Science University of Cape Town
spellingShingle Financial Mathematics
Jama, Siphamandla
An alternative model for multivariate stable distributions
thesis_degree_str Master's
title An alternative model for multivariate stable distributions
title_full An alternative model for multivariate stable distributions
title_fullStr An alternative model for multivariate stable distributions
title_full_unstemmed An alternative model for multivariate stable distributions
title_short An alternative model for multivariate stable distributions
title_sort alternative model for multivariate stable distributions
topic Financial Mathematics
url http://hdl.handle.net/11427/8959
work_keys_str_mv AT jamasiphamandla analternativemodelformultivariatestabledistributions
AT jamasiphamandla alternativemodelformultivariatestabledistributions