Decision Methods Of Coal Resources Investment Based On Real Options

In the context of complicated international energy situation and domestic economyslowdown, China’s Coal Resource Investment (CRI) is affected by many uncertain factors.How to take advantage of these uncertainties, and avoid and transform those risksscientifically and reasonably they bring are the key issues in CRI. Because of fixed parameter,reversible investment, rigid decision-making, the traditional Net Present Value (NPV) isunable to assess the value of the project when decision-makers adopt the flexible strategyunder conditions of uncertainty, and leads to the evaluation results deviated from the truevalue of the project. In view of this, based on Real Option Theory, the paper integrates suchknowledge which contains investment appraisal theory, resource economics theory, statisticaltheory, stochastic process theory, and studies the method of CRI decision by theoretical andempirical, qualitative and quantitative analysis, the main results of the research are as follows.(1) Revealing the formation mechanism of CRI options valueOriginal research for mineral resources, especially the formation mechanism of CRIoption value, is still a lack of depth. In this paper, based on the defining the CRI, identifyingthe main uncertainty factors affecting CRI value and analyzing the options characteristics ofthe CRI project, we find that there are a variety of real options such as delayed option,expanded option, contracted option, stop-start option and abandoned option etc whichdistributed in the process of the CRI. And the theory that Coal resources investment process isto manage these real options is proposed. If ignoring the real options, the investment value ofthe coal resources must be underestimated. Therefore, the CRI decision-making process isbuilt based on real options. Studies have shown that CRI is a complete value chain, the valueof CRI project is neither the sum of static NPV of the investment project at each stage nor thesimple addition together for every single real options above, but a dynamic changing process of multi-stage and multi-factor compound option.(2) Setting up the decision model of coal resources exploration investmentThe original research mostly regards coal reserves as the underlying assets, and thedecision model of Coal Resources Exploration Investment (CREI) is set up accordingly. Inthis paper, as the underlying assets, exploration results are more in line with the actualsituation of the coal resources exploration investment. Based on analyzing uncertainties andoption characteristics of CREI project, three models are established, respectively, includingthe single-factor evaluating model of CREI project based on random changes in explorationresults transfer prices, the two-factor evaluating model of CREI project based on randomchanges in exploration results transfer prices and coal resources hosting condition, themulti-factor evaluating model of CREI project based on random fluctuation of explorationresults transfer prices, coal resources hosting condition, survey costs and interest rates.Through case studies, we have tested the effectiveness of the above three models. Wecompare assessment results of three models, then find while we join coal resources hostingcondition volatility in the single-factor model in the later stage of CREI project, it will turninto the two-factor model, and project critical value can change greatly. However, thetwo-factor model will become the multi-factor model by adding convenience yields, interestrates and survey costs.The difference in estimated critical value would not be so great, weinfer that coal resources hosting condition volatility has a significant role in the critical valueof CREI project.(3) Setting up the decision model of coal resources development investmentThe original research mostly considers the impact of random changes in the price of coalon Coal Resources Development Investment (CRDI), and the single-factor evaluating modelof CRDI is formulated accordingly. In this paper, considering the impact of differentuncertainties on CRDI, three models are set up namely, the single-factor evaluating model, thetwo-factor evaluating model and the multi-factor evaluating model respectively. Thesingle-factor evaluating model of CRDI project based on coal prices follows a mixedBrownian motion/jump process. The two-factor evaluating model of CRDI project based onrandom changes between coal prices and development costs, coal prices and convenienceyields. The multi-factor evaluating model of CRDI project based on random fluctuation ofcoal prices, convenience yields, interest rates and production costs, and the model is solved byusing the least squares Monte Carlo method. We use the case studies to test the validity of themodels. A comparison of three models of evaluation results, we find that increasinguncertainty will cause the critical value of the CRDI project to change greatly, the difference in estimated critical value would be large among the single-factor evaluating model, thetwo-factor evaluating model and the multi-factor evaluating model. It can be seen thatuncertain factors play a role in the value of the CRDI project.(4) Setting up the decision model of coal resources deep-processing investmentThe original research mostly considers the impact of random variation of output priceson coal resources deep-processing investment (CRDPI), and the single-factor evaluatingmodel of CRDPI is formulated. In this paper, considering the impact of different uncertaintieson CRDPI, three models are set up accordingly. The single-factor evaluating model of CRDPIproject based on random changes in products output, the two-factor evaluating model ofCRDPI project based on random changes between output prices and production costs, outputprices and interest rates, the multi-factor evaluating model of CRDPI project based on randomfluctuation of output prices, convenience yields, interest rates and production costs. Throughcase studies, we have tested the effectiveness of the above three models. The sensitivityanalysis shows that the project critical value will increase when we change jump amplitudefrom negative to positive. Output prices volatility and output costs volatility have a positiveeffect on the project critical value and the value of the project. The convenience yields have anegative effect on the project critical value, while would positively affect the value ofthe project. The interest rates have a positive impact on the project critical value, whichnegatively affect the value of the project. The correlation coefficient of output prices volatilityand output costs volatility has a negative effect on the value of the project.The above results will provide theoretical guidance for China’s CRI evaluation, and helpinvestor make a scientific and rational decision.