Developing a share portfolio selection framework for the mining sector
Kleynhans, Johan Andries
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In order to make the right investment decision about future share prices one must be able to predict accurately. Nonetheless investment will still be bound to risk and volatility due to share market fluctuations. Therefore in the investment industry future share price prediction relies crucially on accurate forecast models. These models are constructed by analysts using a set of current and historical data available in order to predict what will play out in the near future. The mining industry within South Africa and globally are experiencing enormous pressure due to commodity price constraints. In order to retain positive investor sentiment towards mining companies, companies are working around the clock to secure dividend pay-out as promised. Profit sharing through dividend pay-out is still a lucrative tool to keep investors within the mining sector. The aim is to develop a share portfolio selection framework based on assertive criteria identified within the mining sector. The criteria will be utilised to develop a framework by which investors can indicate shares with high share price growth potential. This framework should reduce the risk of selecting poor performing shares within the mining sector. Seventeen independent variable/criteria were selected in the process to develop a regression model. Only five variables/criteria were included in the final regression model namely: Price/Book value, Price/Earnings ratio, Dividend/Share, Revenue and Margin of Safety. Only five years produced workable results for multiple regression models. It can therefore be concluded that no constant repeatable share portfolio selection framework for the mining sector in South Africa could be developed with the criteria set out in this research study.