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dc.contributor.advisorNel, Ines
dc.contributor.authorOlivier, Natasja
dc.date.accessioned2014-08-14T08:45:06Z
dc.date.available2014-08-14T08:45:06Z
dc.date.issued2011
dc.identifier.urihttp://hdl.handle.net/10394/11095
dc.descriptionThesis (MBA)--North-West University, Potchefstroom Campus, 2012en_US
dc.description.abstractShareholder wealth creation is a topic taught in MBA programmes. This paper documents the development of a share selection framework in order to construct an alpha portfolio within the general mining sector of the JSE limited. The relationship between fundamental analysis indicators, such as book value per share, earnings per share and intrinsic value, and the average annual share price is determined in order to build a linear regression model. The model is applied to the general mining sector to test its effectiveness. Criteria are set for each indicator to identify companies from this sector for inclusion in the final portfolio. A portfolio’s risk is determined by the proportions of the individual securities, their variances, and their co-variances. Markowitz (1952) quantitatively demonstrated the benefits of diversification in order to reduce risk (volatility) and increase return. This theory was put to the test by comparing individual shares’ average volatilities against the diversified portfolio’s average volatilities for similar and/or improved returns. A weighted average portfolio, with the lowest standard deviation, consisting of four shares identified from the selection framework, was constructed. The portfolio’s average annual growth rate was benchmarked against the JSE All Share Index average annual growth rate to evaluate returns over a ten year period. The research hypothesis, namely shareholder wealth creation in an alpha portfolio, was reached: the final portfolio outperformed the JSE All Share Index annual growth rate in seven out of the ten evaluated years.en_US
dc.language.isoenen_US
dc.titleA share selection framework for investors in the mining sector of JSE (Ltd)en
dc.typeThesisen_US
dc.description.thesistypeMastersen_US
dc.contributor.researchID10186468 - Nel, Ines (Supervisor)


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