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Segilola gold mine valuation using Monte Carlo simulation approach

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Abstract

The Segilola gold mine has been valued in this work to determine its viability using Monte Carlo simulation approach. To achieve this, a base case discounted cash flow (DCF) model was developed for the project from which sensitivity analysis was conducted to determine the value drivers in the project. Using Palisade's @Risk 6.0 software and setting suitable probability distribution function for the value drivers of the project, Monte Carlo simulation was used to calculate the statistical forecast of the project value. The base case DCF analysis gave a negative net present value (NPV) of US$−7.46 million. The sensitivity analysis showed that the input parameters: gold price, gold grade, strip ratio, and operating costs are the value drivers of the project. A mean NPV of US$30.79 million was obtained for the project with a standard deviation of US$58.26 million after running the Monte Carlo simulation. The simulation result also showed that the probability of achieving positive NPV (profit) in the project is 69.2 % and probability of loss of money is 30.8 %.

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Correspondence to Chima C. Ugwuegbu.

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Ugwuegbu, C.C. Segilola gold mine valuation using Monte Carlo simulation approach. Miner Econ 26, 39–46 (2013). https://doi.org/10.1007/s13563-013-0030-8

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  • DOI: https://doi.org/10.1007/s13563-013-0030-8

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