The portfolio selection problem has been widely understood and practised for millennia,
but it was rst formalised by Markowitz (1952) with the proposition of a risk-reward
trade-o model. Since then, portfolio selection models have continued to evolve. The
general consensus is that three objectives, to maximise the uncertain Rate Of Return
(ROR), to maximise liquidity and to minimise risk, should be considered.
It was found that there are opportunities for improvement within the existing
portfolio selection models. This can be attributed to three gaps within the existing
models. Generally, existing portfolio selection models are generic, especially in how they
incorporate risk, they generally do not incorporate Socially Responsible Investing (SRI),
and generally they are considered to be unvalidated. This dissertation set out to address
these gaps and compare the real-world performance of generic and individualised portfolio
selection models.
A new method of accounting for risk was developed that consolidates the portfolio's
market risk with the investor's nancial risk tolerance. Two portfolio selection models
that incorporate individualised risk and SRI objectives were developed. These two models
were called the risk-adjusted and social models, respectively. These individualised models
were compared to an existing generic Markowitz model.
These models were formulated using stochastic goal programming. A sample of
208 companies JSE Limited companies was selected and two independent datasets
were extracted for these companies, a training (2010/01/01 { 2016/12/31) and testing
(2017/01/01 { 2019/12/31) dataset. The models solved were in LINGO using the training
dataset and tested on an unknown future by using the testing dataset.
It was found that in the training period, the individualised risk-adjusted model
outperformed the generic Markowitz model and the individualised social model.
Furthermore, it was found that it would not be bene cial for an investor to be Socially
Responsible (SR). Nevertheless, investors invest to achieve their ROR and SRI goals in the
future, not in the present. Thus, it was necessary to evaluate how the portfolios selected
by all three models would have performed in an unknown future.
In the testing period, both the generic Markowitz model and the risk-adjusted models
had dismal performance and were signi cantly outperformed by the South African market
and unit trusts. Thus, these models are not useful or suitable for their intended purpose.
On the contrary, the social model portfolios achieved high ROR values, were SR, and
outperformed the market and the unit trusts. Thus, this model was useful and suitable for
its intended purpose. The individualised social model signi cantly outperformed the other
two models. Thus, it was concluded that an individualised approach that incorporates SRI
outperforms a generic portfolio selection approach.
Given its unparalleled performance and novel model formulation, the social model
makes a contribution to the eld of portfolio selection. This dissertation also highlighted
the importance of testing portfolio selection models on an unknown future and
demonstrated the potentially horri c consequences of neglecting this analysis. / Dissertation (MEng (Industrial Engineering))--University of Pretoria 2021. / Industrial and Systems Engineering / MEng (Industrial Engineering) / Unrestricted
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:up/oai:repository.up.ac.za:2263/78702 |
| Date | January 2021 |
| Creators | Van Niekerk, Melissa |
| Contributors | Bean, Wilna, melissa@mjvn.net, Trent, Nadia M. |
| Publisher | University of Pretoria |
| Source Sets | South African National ETD Portal |
| Language | English |
| Detected Language | English |
| Type | Dissertation |
| Rights | © 2019 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. |
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