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Real Option Valuation of Mineral Exploration/Mining Projects using Decision Trees - Differentiating Market Risk from Private Risk

机译:使用决策树进行矿产勘探/采矿项目的实物期权评估-将市场风险与私人风险区分开来

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摘要

Only a few complex real options can be valued using closed-form equations, such as the Black and Scholes formula, because these algorithms are restrictive and prevent the construction of practical project evaluation models. Although a binomial lattice method paired with the 'risk-neutral probability' provides an easier and flexible modelling of exploration and mining projects, it has limitations when projects are complex, long-lived and influenced by the interplay of various market and private uncertainties. In order to overcome these limitations, modern decision tree software using dynamic programming capability can be used for real option valuations. This is a powerful computational tool in which the impact of various sources of uncertainties can be differentiated, so that the optimal decision path can be explicitly displayed visually. There has been significant academic controversy surrounding whether different real option (RO) valuation methods would lead to different real option values (ROV). This paper, using a realistic copper mining example, demonstrates that as long as the same degree of subjectivity and consistency are used in different real option valuation methods, they yield the same result. This conclusion is valid irrespective of whether the cash flow volatility generated by various sources of uncertainties is handled in an aggregated or in an explicit and differentiated manner. This paper compares two choices for an investor either to 'buy now and develop' a project or to enter into a 'two-year option to purchase' after the proponents have developed it. It also shows how significantly different net after-tax operating cash flows may be generated by these different choices on the same underlying asset represented by the project. This is due to the difference in the amount and timing of the relevant capital investments affecting the depreciation and amortisation charges and as a consequence, the income tax paid.
机译:使用闭式方程式(例如Black和Scholes公式)只能对几个复杂的实物期权进行估值,因为这些算法具有限制性,并妨碍了实际项目评估模型的构建。尽管将二项式格点法与“风险中性概率”结合使用,可以更轻松,灵活地对勘探和采矿项目进行建模,但是当项目复杂,寿命长且受各种市场和私人不确定性的相互作用影响时,它具有局限性。为了克服这些限制,可以将使用动态编程功能的现代决策树软件用于实物期权评估。这是一个功能强大的计算工具,其中可以区分各种不确定性源的影响,从而可以在视觉上显式显示最佳决策路径。关于不同的实物期权(RO)评估方法是否会导致不同的实物期权价值(ROV),存在着重大的学术争议。本文以一个现实的铜矿开采为例,表明只要在不同的实物期权估值方法中使用相同程度的主观性和一致性,它们就会产生相同的结果。该结论是有效的,无论由各种不确定性来源产生的现金流量波动是以汇总方式还是以明确方式和差异方式进行处理。本文对投资者的两种选择进行了比较,要么是“立即购买并开发”一个项目,要么是在支持者开发项目后进入“两年购买”的选择。它还显示了这些不同选择对项目所代表的同一基础资产产生的税后净营业现金流量有何显着差异。这是由于相关资本投资的金额和时间差异影响了折旧和摊销费用,并因此影响了所缴纳的所得税。

著录项

  • 来源
    《Project evaluation conference 2012.》|2012年|p.177-188|共12页
  • 会议地点 Melbourne(AU)
  • 作者

    P Guj; A Chandra;

  • 作者单位

    Centre for Exploration Targeting, School of Earth and Environment, The University of Western Australia, Crawley WA 6009;

    Centre for Exploration Targeting, Department of Mineral and Energy Economics, Graduate School of Business, Curtin University, 78 Murray Street, Perth WA 6000;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 地质、矿业;地质、矿业;
  • 关键词

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