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Optimal portfolio performance constrained by tracking error

Dissertation (MSc (Financial Engineering)--University of Pretoria, 2020.

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Other Authors: Van Vuuren, Gary
Format: Thesis
Language:English
Published: University of Pretoria 2021
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access_status_str Open Access
author2 Van Vuuren, Gary
author_browse Van Vuuren, Gary
author_facet Van Vuuren, Gary
collection Thesis
dc_rights_str_mv © 2020 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria.
description Dissertation (MSc (Financial Engineering)--University of Pretoria, 2020.
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institution University of Pretoria (South Africa)
language English
last_indexed 2026-06-10T12:39:29.475Z
license_str Other — see source repository
provenance_str_mv Harvested via OAI-PMH from UPSpace — University of Pretoria Institutional Repository
publishDate 2021
publishDateRange 2021
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publisher University of Pretoria
publisherStr University of Pretoria
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source_str UPSpace — University of Pretoria Institutional Repository
spelling oai:repository.up.ac.za:2263/78230 Optimal portfolio performance constrained by tracking error Van Vuuren, Gary Gunning, Wade Michael Tracking Error Omega function Portfolio Optimisation UCTD Dissertation (MSc (Financial Engineering)--University of Pretoria, 2020. Maximising investment returns is the primary goal of asset management but managing and mitigating portfolio risk also plays a significant role. Successful active investing requires outperformance of a benchmark through skilful stock selection and market timing, but these bets necessarily foster risk. Active investment managers are constrained by investment mandates such as component asset weight restrictions, prohibited investments (e.g. no fixed income instruments below investment grade) and minimum weights in certain securities (e.g. at least 𝑥�% in cash or foreign equities). Such strategies' portfolio risk is measured relative to a benchmark (termed the tracking error (TE)) – usually a market index or fixed weight mix of securities – and investment mandates usually confine TEs to be lower than prescribed values to limit excessive risk taking. The locus of possible portfolio risks and returns, constrained by a TE relative to a benchmark, is an ellipse in return/risk space, and the sign and magnitude of this ellipse's main axis slope varies under different market conditions. How these variations affect portfolio performance is explored for the first time. Changes in main axis slope (magnitude and sign) acts as an early indicator of portfolio performance and could therefore be used as another risk management tool. The mean-variance framework coupled with the Sharpe ratio identifies optimal portfolios under the passive investment style. Optimal portfolio identification under active investment approaches, where performance is measured relative to a benchmark, is less well-known. Active portfolios subject to TE constraints lie on distorted elliptical frontiers in return/risk space. Identifying optimal active portfolios, however defined, have only recently begun to be explored. The Ω ratio considers both down and upside portfolio potential. Recent work has established a technique to determine optimal Ω ratio portfolios under the passive investment approach. The identification of optimal Ω ratio portfolios is applied to the active arena (i.e. to portfolios constrained by a TE) and it is found that while passive managers should always invest in maximum Ω ratio portfolios, active managers should first establish market conditions which determine the sign of the main axis slope of the constant TE frontier) and then invest in maximum Sharpe ratio portfolios when this slope is > 0 and maximum Ω ratios when the slope is < 0. Mathematics and Applied Mathematics 2021-02-03T12:41:09Z 2021-02-03T12:41:09Z 2020-10-20 Dissertation http://hdl.handle.net/2263/78230 en © 2020 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. 81 Pages PDF application/pdf University of Pretoria
spellingShingle Tracking Error
Omega function
Portfolio Optimisation
UCTD
Optimal portfolio performance constrained by tracking error
title Optimal portfolio performance constrained by tracking error
title_full Optimal portfolio performance constrained by tracking error
title_fullStr Optimal portfolio performance constrained by tracking error
title_full_unstemmed Optimal portfolio performance constrained by tracking error
title_short Optimal portfolio performance constrained by tracking error
title_sort optimal portfolio performance constrained by tracking error
topic Tracking Error
Omega function
Portfolio Optimisation
UCTD
url http://hdl.handle.net/2263/78230