The research is a quantitative study that formulates an approach to future
portfolio asset allocations within the South African domestic equity market, and
the diversification of assets across global markets, specifically the U.S.A. The
research takes the view that investors are rational, have a long term investment
horizon and seek investment wealth maximisation by applying a sustainable
investment strategy towards the ongoing management of the portfolio.
Investors experience a significant negative divergence in investment outcomes
relative to the potentially achievable result. This negative divergence is a result
of the lack of a strategic approach to, and an understanding of asset allocations,
and the lack of a sustainable approach to the management of a portfolio.
Repetitive sub-optimal investment performance, below the levels of inflation, is
an investment disincentive with negative micro and macro implications.
The purpose of the study is therefore to address the issue sub-optimal
investment performance through the effective application of a strategy that
includes the integration of the mean-variance model through the use of a mean-variance
optimiser, using resampled data inputs, the mean reversion of
markets, passive investment management, appropriate asset class selection
and the ongoing management of a portfolio, using both calendar and contingent
rebalancing techniques, and passive formula strategies.
The challenge is accordingly to develop a reliable asset allocation model that
accommodates past performance, and which is stable enough to produce
optimised forward-looking investment portfolios, which are able to address the
issue of optimal asset allocation and selection, within a global context, and
which produce optimised investment outcomes, taking cognisance of the fact
that the future is unknowable and dynamic.
The research methodology makes a positivist assumption that something exists
and can be numerically tested. In this regard various portfolios are constructed,
using passive investment instruments, in accordance with mean-variance model
principles, using resampled data inputs to minimise the instability of the mean-variance
optimiser. This resampling process is fundamental to the research,
and incorporates the use of a stochastic simulator. A unique aspect of the
research was solving the issue of multiple market integration particularly when
the domestic markets are comprised of multiple asset classes. Finally, the
resultant resampled efficient portfolios are compared to control portfolios in
order to ascertain whether the resampling process indeed offers a return
premium.
Due to the dynamic nature of equity markets contingent and calendar
rebalancing strategies are applied to the asset allocation in order to maintain an
optimal portfolio. This dynamism may necessitate the adjustment of asset
allocations. The test for asset allocation optimality takes the form of measuring
portfolio outcome correlations to the actual market outcome. Where the portfolio is sub-optimal the asset allocations are redetermined, otherwise the portfolio is
merely rebalanced to the original asset allocations.
Regarding the management of the portfolio a value averaged passive formula
strategy is applied. This process acknowledges that markets may behave
stochastically over the short term, therefore a predetermined value line is
derived that the portfolio is to achieve. This value line is based on a long term
equity premium plus inflation. Should the portfolio breach the value line on the
upside a portion of the investment is liquidated, conversely when the portfolio
fails to reach the value line the portfolio is elevated to the value line by means of
increasing the investment.
The results of the research manifest unambiguous results in favour of
resampled portfolios. In this regard, therefore, data resampling does seem to
produce stable portfolio results that are effective at capturing a higher
proportion of future returns than a simple market portfolio. Furthermore, the
rebalancing process, although not absolutely perfect, does provide a level of
adjustment to the asset allocation to ensure optimality. Finally, management of
the portfolio through value averaging unambiguously provides an internal rate of
return in excess of a portfolio that is allowed to stochastically rise and fall.
In summary, the integration of the identified processes clearly provides a
performance premium in excess of alternative approaches, and within a
framework that is sustainable from period to period.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:ufs/oai:etd.uovs.ac.za:etd-09302005-101449 |
| Date | 30 September 2005 |
| Creators | Pawley, Mark Gary |
| Contributors | Prof H van Zyl, Dr P Greeff |
| Publisher | University of the Free State |
| Source Sets | South African National ETD Portal |
| Language | en-uk |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.uovs.ac.za//theses/available/etd-09302005-101449/restricted/ |
| Rights | unrestricted, I hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to University Free State or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report. |
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