Multiple Volatility Real Options Approach to Investment Decisions Under Uncertainty

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.

Automated summary

This paper presents a novel multiple volatility real options approach (MVR) to evaluate investment projects. MVR uses a decision tree composed of synthetic tree components to approximate the project value induced by different uncertainties. Through Monte Carlo simulation, MVR generates a multidimensional surface representing enhanced net present value (ENPV) as a function of each uncertainty. MVR provides a more accurate valuation and robust investment decisions.