Multiple Volatility Real Options Approach to Investment Decisions Under Uncertainty

Atul Chandra (), Peter Hartley and Gopalan Nair ()
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Atul Chandra: School of Business and Law, Edith Cowan University, Perth, Western Australia 6027, Australia
Gopalan Nair: Department of Mathematics and Statistics, The University of Western Australia, Perth, Western Australia 6009, Australia

Decision Analysis, 2022, vol. 19, issue 2, 79-98

Abstract: 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.

Keywords: real options; investment; decision making; real option decision tree; natural resources; asset pricing (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:ordeca:v:19:y:2022:i:2:p:79-98

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