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Robust portfolio construction using sorting signatures

Includes bibliographical references.

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Bibliographic Details
Main Author: Kasenene, Lillian
Other Authors: Bradfield, Dave
Format: Thesis
Language:English
Published: Division of Actuarial Science 2014
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access_status_str Open Access
author Kasenene, Lillian
author2 Bradfield, Dave
author_browse Bradfield, Dave
Kasenene, Lillian
author_facet Bradfield, Dave
Kasenene, Lillian
author_sort Kasenene, Lillian
collection Thesis
description Includes bibliographical references.
format Thesis
id oai:open.uct.ac.za:11427/8527
institution University of Cape Town (South Africa)
language eng
last_indexed 2026-06-10T12:51:28.109Z
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 Division of Actuarial Science
publisherStr Division of Actuarial Science
record_format dspace
source_str UCTD — University of Cape Town Open Access Repository
spelling oai:open.uct.ac.za:11427/8527 Robust portfolio construction using sorting signatures Kasenene, Lillian Bradfield, Dave Bailey, Geraldine Includes bibliographical references. Mean-variance analysis introduced by Harry Markowitz has been criticised in the past mainly due to the counter-intuitive and unstable nature of the resultant portfolios from the optimisation. These disappointing results have been linked to the presence of estimation error in the estimates of the expected returns and covariances which serve as input to the optimisation. Several attempts have been made to produce more reliable estimates, with a significant amount of effort and resources placed in estimation of expected returns, which is generally a more difficult task than estimation of covariances. Almgren and Chriss (2006) provide a methodology for portfolio selection in which the order of expected returns replaces the numerical values of the returns. This framework allows full use of the covariance matrix, in a method analogous to mean-variance optimisation. We adopt this framework in our analysis together with the robust optimisation technique introduced by Golts and Jones (2009) which improves the estimate of the covariance matrix by direct modification in the optimisation process. Golts and Jones (2009) argue that a reduction of the angle between the input return forecasts and the output portfolio positions results in more investment relevant portfolios, inline with the investment manager's insights. They relate this angle to the condition number of the covariance matrix and use robust optimisation to improve the conditioning of this matrix. Assuming perfect alpha foresight of an investment manager, we apply a combination of the techniques of Almgren and Chriss (2006) and Golts and Jones (2009) to South African equity data and show that the resultant robust portfolios, though conservative in their risk-adjusted return statistics, are more diversified and exhibit lower leverage than mean-variance portfolios. We further show that independent of the optimisation method, there is a marginal difference in the performance of portfolios created using ordering information and actual returns. 2014-10-17T10:09:56Z 2014-10-17T10:09:56Z 2014 Master Thesis Masters MPhil http://hdl.handle.net/11427/8527 eng application/pdf Division of Actuarial Science Faculty of Commerce University of Cape Town
spellingShingle Kasenene, Lillian
Robust portfolio construction using sorting signatures
thesis_degree_str Master's
title Robust portfolio construction using sorting signatures
title_full Robust portfolio construction using sorting signatures
title_fullStr Robust portfolio construction using sorting signatures
title_full_unstemmed Robust portfolio construction using sorting signatures
title_short Robust portfolio construction using sorting signatures
title_sort robust portfolio construction using sorting signatures
url http://hdl.handle.net/11427/8527
work_keys_str_mv AT kasenenelillian robustportfolioconstructionusingsortingsignatures