Real option valuation of an Indian iron ore deposit through system dynamics model

Tanmoy Hazra, Biswajit Samanta and Kaushik Dey

Resources Policy, 2019, vol. 60, issue C, 288-299

Abstract: The values of the mine planning parameters are changed dynamically over the life of mine. These values are not exactly known at the time of preparation of long-term mine plan and valuation of the mine. Hence, future values of these parameters are to be forecasted which results in the uncertainties of parameter estimation. Uncertainties in parameter set thus become a grave concern to a mine planner. The conventional deterministic NPV method fails to provide the desired solution in many situations as it captures neither the uncertainties nor the dynamic nature of the parameters. Realizing the above facts, few researchers approached the problem using stochastic NPV method of evaluation. They mainly considered price and metal uncertainties in the development of stochastic evaluation models. Real Option Valuation (ROV) is a much more pragmatic approach to solve this problem. By exercising different options such as continue, deferral, expand and shutdown optimally, the ROV approach adds more value to a project. In addition, when the ROV is integrated with System Dynamics Model (SDM) for simulation of various stochastic planning parameters, it strengthens the method of project valuation. In the present study, metal price, capital and operating costs, and other relevant planning parameters are simulated in SDM platform along with ore reserve by conditional simulations for evaluation of an iron ore project. The study results indicate that the ROV method yields 10% higher NPV than the NPV obtained in the stochastic NPV method for this specific case study mine.

Keywords: Real option valuation; System dynamics model; Conditional simulation; Geostatistical simulation; Mean reversion; Triangular distribution; NPV model; LSM method (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (8)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jrpoli:v:60:y:2019:i:c:p:288-299

DOI: 10.1016/j.resourpol.2019.01.002

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