摘要
在国际能源形势复杂多变、国内经济增速放缓的背景下，我国煤炭资源投资受诸多不确定性因素影响。如何把握这些不确定性因素并科学合理规避、转化其所带来的风险，是煤炭资源投资中所面临的关键问题。传统净现值法建立在“参数固定、投资可逆、刚性决策”之基础上，无法评估在不确定性条件下决策者采取“灵活”或“柔性”经营策略时所蕴含的项目价值，从而导致其评估结果偏离了项目的真正价值。鉴于此，本文基于实物期权思想，综合运用投资评价理论、资源经济学理论、统计学原理、随机过程理论等知识，采用理论与实证、定性与定量分析相结合的研究方法对煤炭资源投资决策方法进行了研究，主要工作和结论如下：
（1）揭示了煤炭资源投资期权价值形成机理
原有研究对于矿产资源特别是煤炭资源投资期权价值形成机理尚缺乏深入探讨。本文在界定煤炭资源投资的基础上，识别了煤炭资源投资项目价值的主要不确定性影响因素，分析了煤炭资源投资的期权特性，辨识出煤炭资源投资过程中分布着延迟期权、扩张期权、收缩期权、停启期权、放弃期权等实物期权。提出煤炭资源投资过程就是管理这些实物期权的过程，忽略上述实物期权，必然低估煤炭资源投资价值。建立了基于实物期权的煤炭资源投资决策流程，研究表明煤炭资源投资是一个完整的价值链，煤炭资源投资项目价值不是各阶段投资项目的静态NPV之和，也不是上述单个实物期权价值的简单相加，而是多阶段多因素复合期权的动态变化过程。
（2）建立了煤炭资源勘查投资决策模型
原有研究多以煤炭资源储量作为标的资产，据此建立勘查投资决策模型。本文提出以勘查成果作为标的资产，更符合煤炭资源勘查投资的实际情况。分别建立了基于勘查成果转让价格随机变动下的煤炭资源勘查投资单因素模型决策模型，基于勘查成果转让价格和煤炭资源赋存条件随机变动下的煤炭资源勘查投资双因素决策模型和基于煤炭价格、煤炭资源赋存条件、勘查成本和利率均随机变动下的煤炭资源勘查投资多因素决策模型模型。通过案例分析，对上述三种模型的有效性进行了检验。对三个模型评估结果相比较后发现，在煤炭资源勘查投资后期，在单因素模型加入煤炭资源赋存条件随机变化，由此变为双因素模型后，项目临界价值发生较大变化，而双因素模型加入利率和勘查成本随机变化，变为多因素模型后，所估算的项目临界价值差异并不是很大，可以认为煤炭资源赋存条件对煤炭资源勘查项目的临界价值具有显著作用。
（3）建立了煤炭资源开发投资决策模型
已有研究多考虑煤炭价格随机变化对煤炭资源开发投资的影响，据此建立开发投资单因素决策模型。本文考虑多种不确定性因素对煤炭资源开发投资的影响，分别建立了基于煤炭价格为混合布朗运动/跳跃过程的煤炭资源开发投资单因素决策模型，基于煤炭价格和开采成本、煤炭价格和便利收益均随机变动模式的煤炭资源开发投资双因素决策模型和基于煤炭价格、便利收益、利率、开采成本均随机变动的煤炭资源开发投资多因素决策模型。通过案例分析，对上述模型的有效性进行了验证。对比三个模型的评估结果可以发现，在不确定性因素逐渐增加的情况下，煤炭资源开发投资项目的临界价值发生了较大变化，单因素与双因素模型、双因素模型与多因素模型的估算结果均有很大差异，这可以看出，各不确定性因素均对煤炭资源开发投资项目价值有较大影响。
（4）建立了煤炭资源深加工投资决策模型
已有研究多考虑产出品价格随机变化对煤炭资源深加工投资的影响，据此建立深加工投资决策单因素决策模型。本文考虑多种不确定性因素对煤炭资源深加工投资的影响，分别建立了基于产出品为随机变动模式的煤炭资源深加工投资单因素决策模型，基于产出品价格和生产成本、产出品价格和利率均为随机变动模式的煤炭资源深加工投资双因素决策模型，基于产出品价格、便利收益、利率、生产成本均为随机变动模式的煤炭资源深加工投资多因素决策模型。通过案例分析，对上述模型的有效性进行了验证。结果表明，随着不确定性影响因素的增加，项目临界价值和产品临界价格均发生了较为明显的提高。同时，对比单因素和双因素模型计算结果的差异，双因素和多因素模型计算结果差异更为显著。
以上研究成果将对我国煤炭资源投资价值评估提供方法上的支持，也将为投资者进行科学合理的战略决策予以帮助。
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 value
Original 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 investment
The 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 investment
The 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 investment
The 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.
引文
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