The Development of Applied Real Options Approaches for the Valuation of Mining Projects

矿业项目估值应用实物期权方法的发展

• 批准号: RGPIN-2017-06627
• 负责人: Lawryshyn, Yuri
• 金额: $ 1.53万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=656851
• 关键词: Development; Applied; Real; Options; Approaches

Real option analysis (ROA) is recognized as a superior method to quantify the value of real-world investment opportunities where managerial flexibility can influence their worth, as compared to standard discounted cash-flow methods typically used in industry. A comprehensive ROA of an oil, gas or mineral mining project can improve the allocation of capital and managerial decision making and the methodology is currently used, to some degree, in the commodity extraction sectors. However, realistic models that try to account for a number of risk factors can be mathematically complex, and in situations where many future outcomes are possible, many layers of analysis may be required. Typically, managers are usually unable to understand the models and dismiss results that seem unintuitive to them. A recent empirical study showed that roughly 35% more value can be extracted from mining operations if managers had made better timing and capacity decisions.******The focus of this proposal is the development of an “intelligent” real options valuation (IROV) methodology geared towards practical use with specific emphasis on mining finance. The overall objective of the proposed research is to develop a methodology and tool that allows managers and engineers to apply ROA in complex, real world settings in the context of the valuation of mining projects. The methodology will be based on sound financial principles utilizing ROA, and will account for both systematic risks associated with economic factors, as well as idiosyncratic risks associated with mining, such as size of deposit and ease (cost) of extraction. While the methodology must account for real world complexities, it must be general and broadly applicable. Finally, the methodology must be such that its fundamentals are easily understood by managers and engineers so that its use is readily adopted.******A key innovation of the model being proposed is the idea of fitting optimal decision making boundaries to optimize the expected value, based on simulated stochastic processes that represent important uncertain factors associated with the mine. Ultimately, the model will consist of hyper-planes that can be used by managers to decide when to build, expand, mothball or abandon. Two approaches to determine these boundaries are proposed: 1) utilizing standard curve fitting and optimization techniques, and 2) utilizing machine learning where an algorithm is utilized to optimize managerial decision making, in the same way as algorithms are utilized to challenge opponents in games such as chess. To the best of my knowledge, the methodology proposed here has not been presented and may provide a key aspect in the practical implementation of ROA. From a training perspective, the research is multi-disciplinary and will provide trainees the opportunity to learn aspects of financial modelling, mining, data analysis, optimization and machine learning.**

与通常在行业中通常使用的标准折扣现金流量方法相比，实际期权分析（ROA）被认为是一种量化现实世界投资机会价值的卓越方法，而管理灵活性可以影响其价值。石油，天然气或矿物采矿项目的全面ROA可以改善资本和管理决策的分配，并且目前在某种程度上在商品提取部门中使用了方法。但是，试图解释许多风险因素的现实模型在数学上可能是复杂的，在许多可能的未来结果的情况下，可能需要许多分析层。通常，管理者通常无法理解模型，并忽略对他们似乎不直觉的结果。最近的一项实证研究表明，如果经理做出了更好的时间和容量决策，则可以从采矿业务中提取大约35％的价值。******这项提案的重点是开发“智能”真实期权价值（IROV）方法，用于实践旨在实用，以特定重点对采矿融资​​进行实际使用。拟议研究的总体目标是开发一种方法和工具，使管理人员和工程师可以在采矿项目价值的背景下在复杂的现实世界中应用ROA。该方法将基于利用ROA的合理财务原则，并将考虑与经济因素相关的系统风险，以及与采矿相关的特殊风险，例如储存量和易于提取（成本）。尽管该方法必须解释现实世界的复杂性，但必须是一般且广泛适用的。最后，该方法必须使经理和工程师很容易理解其基本原理，以便容易采用其使用。****** ******对所提出的模型的关键创新是拟合最佳决策的概念，以制定最佳决策，以优化预期价值，基于代表与我的重要因素相关的随机过程。最终，该模型将由管理人员可以使用何时建立，扩展，封存或放弃的超级播放器组成。提出了两种确定这些边界的方法：1）利用标准曲线拟合和优化技术，以及2）使用机器学习，该算法被利用算法来优化管理决策，就像算法相同的方式来挑战诸如Chess之类的游戏中的选项。据我所知，此处提出的方法尚未提出，并且可能在ROA的实际实施中提供了一个关键方面。从培训的角度来看，这项研究是多学科的，将为受训者提供学习财务建模，采矿，数据分析，优化和机器学习方面的机会。**