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Robust beta estimation and applications

Bibliography: leaves 92-94.

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Main Author: Khan, Mohamed Rezah
Other Authors: Troskie, Casper G
Format: Thesis
Language:English
Published: Department of Statistical Sciences 2014
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access_status_str Open Access
author Khan, Mohamed Rezah
author2 Troskie, Casper G
author_browse Khan, Mohamed Rezah
Troskie, Casper G
author_facet Troskie, Casper G
Khan, Mohamed Rezah
author_sort Khan, Mohamed Rezah
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description Bibliography: leaves 92-94.
format Thesis
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institution University of Cape Town (South Africa)
language eng
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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
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spelling oai:open.uct.ac.za:11427/8593 Robust beta estimation and applications Khan, Mohamed Rezah Troskie, Casper G Statistical Sciences Bibliography: leaves 92-94. Modern portfolio theory was developed by Harry Markowitz more than forty years ago and is now considered to be an indispensable tool in portfolio construction. Sharpe introduced the index models as a simplification of the original Markowitz formulation, as this required fewer parameters to be estimated. One of the premises underlying the Sharpe Index model was that the returns of shares and market proxies followed a normal distribution and under this assumption, model parameters could best be estimated using Ordinary Least Squares (OLS) regression. More recent empirical evidence has however cast doubt over the assumption of normality and has suggested that market returns tend to be non-normal. If the assumption of normality is no longer upheld then OLS or Maximum Likelihood Estimates may no longer produce the best estimates of parameters and hence may compromise optimal portfolio constructions. In addition to the parameter estimation problems, at the time of the initial formulation of the portfolio models, managers were not allowed to participate in short sales (selling a share one does not own). This practice is now quite common in most developed markets and any portfolio formulation model needs to be generalised to allow for this. Empirical studies have shown that share returns and the returns of market proxies do not follow a normal distribution but rather seem to follow a skew distribution and has long tails. It is the aim of this thesis to explore robust regression procedures which should be an improvement of OLS when the data does not come from a normal distribution. The robust regression procedures will then be used to estimate the parameters used in the Sharpe Index models and examine whether or not they aid in the portfolio construction process. The robust procedures will be applied to the classical portfolio formulations as well as the generalised models. 2014-10-18T05:55:26Z 2014-10-18T05:55:26Z 2003 Master Thesis Masters M http://hdl.handle.net/11427/8593 eng application/pdf Department of Statistical Sciences Faculty of Science University of Cape Town
spellingShingle Statistical Sciences
Khan, Mohamed Rezah
Robust beta estimation and applications
thesis_degree_str Master's
title Robust beta estimation and applications
title_full Robust beta estimation and applications
title_fullStr Robust beta estimation and applications
title_full_unstemmed Robust beta estimation and applications
title_short Robust beta estimation and applications
title_sort robust beta estimation and applications
topic Statistical Sciences
url http://hdl.handle.net/11427/8593
work_keys_str_mv AT khanmohamedrezah robustbetaestimationandapplications