Abstract

The end of the 2000s commodity super cycle resulted in all-time high market values for most commodity based companies, followed by a rapid decline in the values post the Global Financial Crisis (GFC) of 2008. The period 2006–2015 was therefore an appropriate review period as it enabled reviewing changes in company value pre and post the GFC.In order to determine the key drivers of company value, financial and production data of four diversified and international mining companies was analyzed. Each of the four companies had a different commodity mix. Due to its suitability for comparison of company value, the market based valuation approach was selected as the appropriate company valuation technique, using enterprise value (EV) as the value metric.Eight potential value drivers were identified. These are production output; commodity price; revenue; earnings before interest, tax, depreciation and amortization (EBITDA) multiple; EBITDA margin; gearing ratio; net debt to EBITDA ratio; and return on capital employed (ROCE). The eight potential value drivers were analyzed firstly using graphical checks, followed by numerical determination of the degree of correlation between each potential value driver and EV using the Pearson correlation coefficient method to confirm the visual analysis. Hypothesis testing was finally done to investigate the strength of the relationships between the potential value drivers and EV.This paper notes some key findings. Revenue, commodity price and EBITDA multiple are primary drivers of value across all four companies, despite their different commodity mix. Of these three drivers revenue is the strongest value driver. It was also noted that the two debt metrics, gearing ratio and net debt to EBITDA, only correlated with EV in times of declining commodity prices and revenue, indicating that value drivers can change with changing economic conditions. It is therefore important for mining companies to periodically identify key value drivers of company value during different economic periods and ensure that they measure their performance based on these.

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