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Evaluation of the mining projects under economic uncertainties using multidimensional binomial tree

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  • Dehghani, Hesam
  • Ataee-pour, Majid
  • Esfahanipour, Akbar

Abstract

Nowadays, economic uncertainties have an indispensable role in mining evaluation projects, so the evaluation of a mining project without considering if the available uncertainties are incorrect and unreliable. Metal price uncertainty and operating costs uncertainty are the most important parameters in economic uncertainty. Numerous research studies have been carried out for price uncertainty, but there is no noticeable research on the simultaneous effects of operating cost and price uncertainties on the evaluation process. To solve this problem, a new evaluation method – pyramid technique – was developed based on the multidimensional binomial tree method. The pyramid technique can evaluate the mining projects under the situation of multi-uncertainties.

Suggested Citation

  • Dehghani, Hesam & Ataee-pour, Majid & Esfahanipour, Akbar, 2014. "Evaluation of the mining projects under economic uncertainties using multidimensional binomial tree," Resources Policy, Elsevier, vol. 39(C), pages 124-133.
    • Handle: RePEc:eee:jrpoli:v:39:y:2014:i:c:p:124-133
    DOI: 10.1016/j.resourpol.2014.01.003
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    Cited by:

    1. Kamel, Ahmed & Elwageeh, Mohamed & Bonduà, Stefano & Elkarmoty, Mohamed, 2023. "Evaluation of mining projects subjected to economic uncertainties using the Monte Carlo simulation and the binomial tree method: Case study in a phosphate mine in Egypt," Resources Policy, Elsevier, vol. 80(C).
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    3. Savolainen, Jyrki, 2016. "Real options in metal mining project valuation: Review of literature," Resources Policy, Elsevier, vol. 50(C), pages 49-65.
    4. Yıldız, Taşkın Deniz, 2022. "Supervisor fund expectation for the guarantee of salaries in the presence of the effect of permanent supervisor salaries on mining operating costs in Turkey," Resources Policy, Elsevier, vol. 77(C).
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    6. Saługa Piotr W. & Kamiński Jacek, 2016. "Hard coal project valuation based on real options approach: multiplicative vs. arithmetic stochastic process," Gospodarka Surowcami Mineralnymi / Mineral Resources Management, Sciendo, vol. 32(1), pages 25-40, March.
    7. Parviz Sohrabi & Hesam Dehghani & Behshad Jodeiri Shokri, 2022. "Determination of optimal production rate under price uncertainty—Sari Gunay gold mine, Iran," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 35(2), pages 187-201, June.
    8. Dehghani, Hesam & Bogdanovic, Dejan, 2018. "Copper price estimation using bat algorithm," Resources Policy, Elsevier, vol. 55(C), pages 55-61.
    9. Krzemień, Alicja & Riesgo Fernández, Pedro & Suárez Sánchez, Ana & Diego Álvarez, Isidro, 2016. "Beyond the pan-european standard for reporting of exploration results, mineral resources and reserves," Resources Policy, Elsevier, vol. 49(C), pages 81-91.
    10. Díaz, Juan D. & Hansen, Erwin & Cabrera, Gabriel, 2020. "A random walk through the trees: Forecasting copper prices using decision learning methods," Resources Policy, Elsevier, vol. 69(C).

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    More about this item

    Keywords

    Metal price uncertainty; Operating costs uncertainty; Multidimensional binomial tree; Evaluation of mining projects;
    All these keywords.

    JEL classification:

    • Q32 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - Exhaustible Resources and Economic Development

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