We present a novel multiple volatility real options approach (MVR) to value investment projects with embedded flexibility and affected by multiple uncertainties. A core innovation is the MVR decision tree composed of MVR synthetic tree components, each reflecting a unique binomial process that approximates a geometric Brownian motion of project value induced by one uncertainty source. MVR uses Monte Carlo simulation to generate volatility of project value log-returns arising from each uncertainty source. MVR produces a multidimensional surface, which is hidden in other approaches, representing enhanced net present value (ENPV) as a function of each uncertainty. It allows the impact of each uncertainty’s volatility on ENPV to be measured through three MVR sensitivity analysis levers. To illustrate MVR, it is applied to a real-world investment project, revealing that MVR provides a more accurate valuation than alternative approaches that do not account for separate impacts of each uncertainty. MVR with its greater veracity, provides robust investment decisions through MVR decision rules.

中文翻译：

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不确定性下投资决策的多重波动实物期权方法

我们提出了一种新颖的多重波动性实物期权方法 (MVR) 来评估具有嵌入式灵活性并受多重不确定性影响的投资项目。一项核心创新是由 MVR 合成树组件组成的 MVR 决策树，每个组件都反映了一个独特的二项式过程，该过程近似于由一个不确定性源引起的项目价值的几何布朗运动。MVR 使用蒙特卡洛模拟来生成项目价值对数回报的波动性，这些波动来自每个不确定性来源。MVR 产生一个隐藏在其他方法中的多维表面，将增强的净现值 (ENPV) 表示为每个不确定性的函数。它允许通过三个 MVR 敏感性分析杠杆来衡量每个不确定性波动对 ENPV 的影响。为了说明 MVR，它应用于现实世界的投资项目，表明 MVR 提供了比不考虑每个不确定性的单独影响的替代方法更准确的估值。MVR 具有更高的准确性，通过 MVR 决策规则提供稳健的投资决策。