Mining Investment Decisions Research Articles

Complementary Development between China and Sub-Sahara Africa: Examining China’s Mining Investment Strategies in Africa

China’s recent national and international regional development strategies emphasize both the deepening of the domestic market and the exploration of new markets and resource suppliers to support China’s industrialization. The cooperation with, and investment in, Africa has become an integrated part of China’s international regional development strategy. Investment in Africa is often the result of a decision process that requires balance among local complex political, economic, social, and geological conditions. Proper decision support analysis is the key for success or failure of complementary development. Based on location theories, the current study analyzes China’s mining investment in Africa and derives a set of indicators to form the basis for evaluating China’s investment strategies in the mining industries in Africa. A multi-criteria decision making (MCDM) approach, the VIKOR method, is applied to evaluate six African countries based on this set of indicators. Results suggest that while resource abundance and value are important factors for mining investment decisions, political stability and local legal system restrictions are weightier in the decision-making process. China’s outward foreign direct investment (OFDI) in mining industries in Africa is more inclined to countries with stable political environment, resource endowment and greater value advantage so that both parties can maximize the benefits from such investment.

Forecasting coking coal prices by means of ARIMA models and neural networks, considering the transgenic time series theory

Price forecasting is a vital matter for mining investment decisions, as it represents the credibility of any financial outcome claimed by the feasibility studies presented to investors in financial markets. Most of these financial studies use forecasts from well-known providers of price assessments and market data that, ultimately, constitute a black box for the investors. This is why, to achieve credibility, user-friendly forecasting techniques through which the future price instability can be bounded are needed.This paper examines the performance in forecasting coking coal prices of traditional time series models, ROBUST models, ARIMA models, generalized regression neural networks (GRNNs) and multi-layer feedforward networks (MLFNs). Two cases are analysed: (1) considering the full time series, and (2) considering the transgenic time series. The latter is based on a theory that addresses the existence of raw material price cycles and the presence of anomalous phenomena due to periods with spiked prices, and it eliminates these periods from the time series to improve the accuracy of the forecasts.At this point, the question of which forecasting performance measure provides a better projection of the errors becomes critical. Keeping in mind that we are focusing on commodity prices and that these results are going to be used for estimating incomes, percentual deviations represent a greater compromise for the forecasts. Among the RMSE, MAE and MAPE, the mean absolute percentage error (MAPE) is the most representative since it is the only one that considers percentual deviations. On the other hand, since the error does not follow a normal distribution, the MAE can be considered to be the second-most representative performance measure, and the RMSE is third.When the full time series is used for the forecast, the GRNN model gives more accurate forecasts than the MLFN model, the ARIMA model, the traditional time series models and the ROBUST model. On the other hand, when the transgenic time series is used for the forecast, the performance of the GRNN model is improved, but, in this case, the ARIMA model achieves a more accurate forecast.

The optimisation rule for investment in mining projects

Investment in mining projects involves significant uncertainty. Project investment is usually high risk, irreversible and challenged by major economic factors. Mining commodity prices in particular always show greater volatility than any other primary products. The variation of these prices is critical in the investment decision of whether the project should go ahead, be abandoned or be delayed. This paper examines the impact of mineral price uncertainty on mining investment decisions using examples of projects in the Asia-Pacific region. Applying the mean reversion (MR) model, the commodity trigger value for investment decisions in each project is determined in the context of operational flexibilities. The findings indicate it is sometimes better to wait for a more suitable time to invest.

Assessing the timing of mining investment under tax policy uncertainty: the case of the Asia-Pacific region

Mining involves the discovery, extraction, and processing of non-renewable resources. The potential of mining revenues to contribute to national economic development is well known, but the allocation of mineral wealth and the concern of increasing resource scarcity have become issues of debate in the mining industry. The purpose of this study is to introduce the binomial decision tree analysis, which is a new approach to mining investment decisions. The examples used examine the impact by a policy change. Using three mining projects in the Asia-Pacific, in Australia, Indonesia and Papua New Guinea, findings about options for the investor suggest it is sometimes better to wait for a more suitable time to invest. Using such knowledge provides the potential to change the investment climate in mining.

Third Order Compound Option Valuation of Flexible Commodity Based Mining Enterprises

Flexibility in managerial decision making will alter the true value of real world projects. Standard actuarial practice for evaluating real-world projects such as commodity based mining operations rely upon Net Present Value methodology and in essence ignore any flexibility available to the operator to vary the project. Real Option analysis rectifies this to allow better evaluation of economic investment decisions by incorporating managerial flexibility into an option pricing framework. In this paper we extend the results of Konstandatos and Kyng (2012) to evaluate a multi-stage compound mining investment decision where the mining operators have the flexibility to delay project commencement as well as options to abandon production and to expand production to a new mining seam if conditions improve. We allow an independent abandonment of the expansion from the underlying project. We demonstrate that the flexibilities considered give rise to a third-order exotic compound structure, which are evaluated in terms of first, second and third order generalised compound option instruments (Konstandatos (2008)). Our novel representations of the project values contain generalizations of standard compound options and are interpretable as generalised call, call-on-call and call-on-call-on-call type options on the mined commodity price. We provide readily-implementable closed-form analytical formulae which are expressed in terms of the uni-variate, bi-variate and tri-variate Normal distribution functions.

A methodology for the management of risk related to uncertainty on the grade of the ore resources

Mining investment decisions for giant mining projects involve an enormous financial risk. Nevertheless, traditional risk evaluation methods are based on Monte Carlo simulation of cash flows and are of little value for risk management. In most mining project scenarios, the main sources of risk are those related to the evaluation of the ore body, specially the grade of the ore reserves. In this study, a new risk management methodology based on conditional simulation is developed to quantify the risk associated with uncertainty on the grade of the ore body. The methodology allows for quantifying risk for each period in the production plan and, therefore, it may be used as a powerful risk management tool to identify risk and ‘risk reduction’ objectives at the prefeasibility stages of a mining project. This model is validated by its application in a case study of a real copper ore body in Chile.

Trinomial tree model of the real options approach used in mining investment price forecast and analysis

In order to effectively avoid the defects of a traditional discounted cash flow method, a trinomial tree pricing model of the real option is improved and used to forecast the investment price of mining. Taking Molybdenum ore as an example, a theoretical model for the hurdle price under the optimal investment timing is constructed. Based on the example data, the option price model is simulated. By the model, mine investment price can be computed and forecast effectively. According to the characteristics of mine investment, cut-off grade, reserve estimation and mine life in different price also can be quantified. The result shows that it is reliable and practical to enhance the accuracy for mining investment decision.

Re-Thinking Kebijakan Pembangunan dalam Perspektif Ekonomi Lokal: Studi Kasus Tambang Emas Batu Gosok – Labuan Bajo – NTT

This paper is a practical-theoretical study towards economic development policy. Unrealistic policy and planning approach, government management close and uncooperative system which considered intervening political interest rather than economic development are as one cause of stagnating economic development in several areas. Economic development that has been established by central government has not able to give velocity acceleration solution in economic development; it is the authority and power divergence that affecting local economic development. Economic policy through mining investment as one strategy development has been approved by district government and investors had affected long polemic. It needs further thought and study related to the policy so it could get the expected result and local economic development. This paper is purposed to give contributed thought of re-thinking policy economic development especially about gold mining investment decision in conservation area of Batu Gosok-Labuan Bajo-NTT.

A model for the evaluation of mining investment proposals under incomplete knowledge

Uncertainty is inherent in mining investment decisions because the knowledge obtainable on conditions which affect choice is limited. The most common techniques for incorporating uncertainty into the investment decision process are here described. The basic features of decision-making under incomplete knowledge are then examined and a new approach to making mining investment decisions is proposed. The proposed approach is based on an a priori ranking of the likelihood of future circumstances and is very straightforward in application. An example is presented and the interpretation of the model is given.