Strategic decision to storage option in gold mines, using the Real option theory

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Article Type:
Case Study (دارای رتبه معتبر)
Abstract:

Mining has been always one of the riskiest and most uncertain activities. Although this uncertainty in conventional economic models (traditional method of net present value or NPV) is considered costly due to the risk of forecasting error, the theory of real options, by considering the value of managerial flexibilities in dealing with these uncertainties, has a positive value. Contrary to the theory of real options, traditional methods of financial evaluations, ignore the value of managerial options and the flexibility of the project. One of the management options in mines, which has been studied in this research and a scientific strategy has been presented for its use, is the authority to store the final product of the mine for a specific period. In this study, assuming that the final product price of the mine follows the Mean Reversion Process (MRP), the type of storage option of the final product of the mine is determined as well as its parameters such as the option time to maturity, option Strick price and the cost of acquisition, and then the option value is evaluated using the binomial lattice network. Finally, using optimization methods, the best market price for gold storage and the expected limits for storage profitability have been determined. The results of this study show that at present, for a mine with sufficient working capital for 6 months of production and a storage cost of $ 5 per ounce, storing the final gold product at a market price of less than 1371 $2022/Oz has a positive (profitable) expected value. Also, the highest value of storage decision was obtained at the world price of 670 $2022/Oz and with the value of 130$2022 per ounce. The relative efficiency of storage is estimated to be up to 21%. It is worth mentioning that to use this article in different mines, its results must be updated by changing the assumptions and new market conditions.

Language:
Persian
Published:
Journal of Aalytical and Numerical Methods in Mining Engineering, Volume:13 Issue: 36, 2023
Pages:
79 to 90
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