Mineral Rights Investment Risk Management Model and Software Implementation
Liming Liu1, Wensi Wang2, Huang Hengjun1
1Capital University of Economics and Business, Beijing, China; 2University College Cork, Cork, Ireland

Mineral rights investment is a business associated with both high risk and high return rate. Pricing strategy is the key component to mineral rights risk management. However, multiple inherent uncertainties of mining industry make this type of investment one of the most challenging tasks in the area of investment management.

The uncertainties (risks) of mineral rights are commonly divided into two major categories: “underground” risks and “above ground” risks. The so-called “underground” risk is the limited understanding of situations to estimate size and grade of the targeted underground mineral deposit. With in-depth exploration of reserves, the estimation will become more accurate. The “above ground” risk is cause by fluctuating market value of minerals, political risk and environmental cost to recover the ore.

This paper introduces a statistical model and its software implementation to analyse the two categories of risks in mineral rights investment. In section 2 of the paper, detailed methods, including normalization of risk variables, method to create the distribution function and analysis of the risk (data clusters) distribution based on empirical Bayes model and frequency distribution analysis, are presented. Section 3 shows two pricing strategies towards highest return rate or lowest risk are used to optimize the decision making capability of the proposed model. Section 4 presents the software implementation of the proposed model.

Since the model is based on historical data and analysis, data gathering and processing are important factors to ensure the precision of the model. In this paper, advanced SD (structure curve integral and dynamic fractal) reserves calculation method is utilized to process the data provided from an industrial co-operator, one of the largest Chinese mineral trading companies. Section 5 shows the evaluation results of the proposed model based on the processed data, the initial results show that the model obtains a high level of accuracy and generalization for different types of minerals.

Keywords: Mineral rights; Risk evaluation; Distribution function; Data processing

Biography: Dr. Liu Liming is a professor and deputy director of statistics department at Capital University of Economics and Business, Beijing, China. Her main research areas cover game theory, applied mathematical statistic study, time series analysis, quantitative finance statistics and econometrics. Dr. Liu devoted more than 20 years of service to statistical research in multiple top universities in China.

She has been principal investigator on more than 10 national research projects and published more than 50 peer-reviewed journal and conference papers. She also wrote and co-authored 5 books in the area of applied statistics. She and her research team have been awarded several prizes over the years, including a national statistics outstanding prize in 2005.

She is a key member of a governmental think tank organized by ministry of finance and state administration of taxation, in responsible of estimate the annual economy performances and taxation of China.