IDEAS home Printed from https://ideas.repec.org/a/eee/jrpoli/v80y2023ics0301420722007097.html
   My bibliography  Save this article

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

Author

Listed:
  • Kamel, Ahmed
  • Elwageeh, Mohamed
  • Bonduà, Stefano
  • Elkarmoty, Mohamed

Abstract

Mining project evaluation is a very complex process and time-consuming task. Any mining project passes through several study stages, like conceptual, preliminary feasibility, and feasibility studies, using a systematic and standardized approach. These studies allow investors to evaluate the exploitations alternatives according to economic and technical criteria to make a better decision. This research aims to study a model for investment risk analysis developed for the case study of “Abu Tartur mining project, Egypt.” Abu Tartur plateau is rich in phosphate rock, turned into phosphoric acid and fertilizers. This study used site-specific data that has been taken from the literature to build evaluation models using the Monte Carlo Simulation (MCS) and the Binomial Decision Tree (BDT) methods. The Discounted Cash Flow (DCF) is considered a benchmark method for all other evaluation methods. The MCS method uses a set of parameters that, in some cases, will give a higher NPV of the project and some others with lower values, but this depends on the probability of the input parameters. The developed evaluation models allowed a specific range of values, with confidence intervals as the MCS model. The advantage of using a probabilistic approach helps in the decisional phase, allowing for a more precise overview of the variability of the final economic value of the mine. Deterministic methods, like the DCF method, offer a solution that is limited to uncertainty analysis.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:jrpoli:v:80:y:2023:i:c:s0301420722007097
    DOI: 10.1016/j.resourpol.2022.103266
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301420722007097
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.resourpol.2022.103266?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Farahani, Hossein & Bayazidi, Shadi, 2018. "Modeling the assessment of socio-economical and environmental impacts of sand mining on local communities: A case study of Villages Tatao River Bank in North-western part of Iran," Resources Policy, Elsevier, vol. 55(C), pages 87-95.
    2. Mathieu Sauvageau & Mustafa Kumral, 2018. "Cash flow at risk valuation of mining project using Monte Carlo simulations with stochastic processes calibrated on historical data," The Engineering Economist, Taylor & Francis Journals, vol. 63(3), pages 171-187, July.
    3. Azimi, Yousuf & Osanloo, Morteza & Esfahanipour, Akbar, 2013. "An uncertainty based multi-criteria ranking system for open pit mining cut-off grade strategy selection," Resources Policy, Elsevier, vol. 38(2), pages 212-223.
    4. Dehghani, Hesam & Bogdanovic, Dejan, 2018. "Copper price estimation using bat algorithm," Resources Policy, Elsevier, vol. 55(C), pages 55-61.
    5. Luiz E. Brandão & James S. Dyer & Warren J. Hahn, 2005. "Using Binomial Decision Trees to Solve Real-Option Valuation Problems," Decision Analysis, INFORMS, vol. 2(2), pages 69-88, June.
    6. 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.
    7. Chen, Yan, 2021. "Evaluating the influence of energy prices on tight oil supply with implications on the impacts of COVID-19," Resources Policy, Elsevier, vol. 73(C).
    8. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
    9. Kloeckner, Jonas & Alves, João Lucas O. & Silva, Flavio H.T. & Guimaraes, Octavio R.A. & Bassani, Marcel A.A. & Costa, Joao Felipe C.L., 2021. "Application of risk assessment to improve sustainability in bauxite mining," Resources Policy, Elsevier, vol. 74(C).
    10. Cox, John C. & Ross, Stephen A. & Rubinstein, Mark, 1979. "Option pricing: A simplified approach," Journal of Financial Economics, Elsevier, vol. 7(3), pages 229-263, September.
    11. Dehghani, Hesam & Ataee-pour, Majid, 2012. "Determination of the effect of operating cost uncertainty on mining project evaluation," Resources Policy, Elsevier, vol. 37(1), pages 109-117.
    12. Dou, Shi-quan & Liu, Jiang-yi & Xiao, Jian-zhong & Pan, Wen, 2020. "Economic feasibility valuing of deep mineral resources based on risk analysis: Songtao manganese ore - China case study," Resources Policy, Elsevier, vol. 66(C).
    13. Kopacz, Michał & Kulpa, Jarosław & Galica, Dominik & Dyczko, Artur & Jarosz, Jacek, 2019. "Economic valuation of coal deposits – The value of geological information in the resource recognition process," Resources Policy, Elsevier, vol. 63(C), pages 1-1.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ronyastra, I Made & Saw, Lip Huat & Low, Foon Siang, 2024. "Monte Carlo simulation-based financial risk identification for industrial estate as post-mining land usage in Indonesia," Resources Policy, Elsevier, vol. 89(C).
    2. Qiu, Hailing & Tseng, Shuan Wei & Zhang, Xuan & Huang, Caiyan & Wu, Kuo-Jui, 2024. "Revealing the compound interrelationships toward sustainable transition in semiconductor supply chain: A sensitivity analysis," International Journal of Production Economics, Elsevier, vol. 271(C).
    3. Raisa Pérez-Vas & Javier Hervés-Estévez & María Dolores Garza Gil & Raquel Fernández-González, 2024. "Valuation of an innovative investment project using real options approach: A case study of a viticulture company in Spain," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 70(2), pages 91-100.
    4. Bijańska, Jolanta & Wodarski, Krzysztof, 2024. "Hard coal production in Poland in the aspect of climate and energy policy of the European Union and the war in Ukraine. Investment case study," Resources Policy, Elsevier, vol. 88(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Savolainen, Jyrki, 2016. "Real options in metal mining project valuation: Review of literature," Resources Policy, Elsevier, vol. 50(C), pages 49-65.
    2. Kim, Amy M. & Li, Huanan, 2020. "Incorporating the impacts of climate change in transportation infrastructure decision models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 134(C), pages 271-287.
    3. Lee, Shun-Chung & Shih, Li-Hsing, 2010. "Renewable energy policy evaluation using real option model -- The case of Taiwan," Energy Economics, Elsevier, vol. 32(Supplemen), pages 67-78, September.
    4. Ardian, Aldin & Kumral, Mustafa, 2020. "Incorporating stochastic correlations into mining project evaluation using the Jacobi process," Resources Policy, Elsevier, vol. 65(C).
    5. Hahn, Warren J. & Dyer, James S., 2008. "Discrete time modeling of mean-reverting stochastic processes for real option valuation," European Journal of Operational Research, Elsevier, vol. 184(2), pages 534-548, January.
    6. Dalbem, Marta Corrêa & Brandão, Luiz Eduardo Teixeira & Gomes, Leonardo Lima, 2014. "Can the regulated market help foster a free market for wind energy in Brazil?," Energy Policy, Elsevier, vol. 66(C), pages 303-311.
    7. Shaton, Katerina, 2015. "Value of Flexibility in Gas Pipeline Investments," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Kersten, Wolfgang & Blecker, Thorsten & Ringle, Christian M. (ed.), Innovations and Strategies for Logistics and Supply Chains: Technologies, Business Models and Risk Management. Proceedings of the Hamburg Internationa, volume 20, pages 333-357, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    8. Schachter, J.A. & Mancarella, P., 2016. "A critical review of Real Options thinking for valuing investment flexibility in Smart Grids and low carbon energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 261-271.
    9. 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).
    10. Inthavongsa, Inthanongsone & Drebenstedt, Carsten & Bongaerts, Jan & Sontamino, Phongpat, 2016. "Real options decision framework: Strategic operating policies for open pit mine planning," Resources Policy, Elsevier, vol. 47(C), pages 142-153.
    11. Kyungwon Kim & Jae Wook Song, 2018. "Managing Bubbles in the Korean Real Estate Market: A Real Options Framework," Sustainability, MDPI, vol. 10(8), pages 1-25, August.
    12. Carlos Andrés Zapata Quimbayo, 2020. "OPCIONES REALES Una guía teórico-práctica para la valoración de inversiones bajo incertidumbre mediante modelos en tiempo discreto y simulación de Monte Carlo," Books, Universidad Externado de Colombia, Facultad de Finanzas, Gobierno y Relaciones Internacionales, number 138, April.
    13. Felipe Isaza Cuervo & Sergio Botero Boterob, 2014. "Aplicación de las opciones reales en la toma de decisiones en los mercados de electricidad," Estudios Gerenciales, Universidad Icesi, November.
    14. Guj, Pietro, 2011. "A practical real option methodology for the evaluation of farm-in/out joint venture agreements in mineral exploration," Resources Policy, Elsevier, vol. 36(1), pages 80-90, March.
    15. Kuangyuan Zhang & Richard Olawoyin & Antonio Nieto & Andrew N. Kleit, 2018. "Risk of commodity price, production cost and time to build in resource economics," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 20(6), pages 2521-2544, December.
    16. 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.
    17. Jorge Tarifa-Fernández & Ana María Sánchez-Pérez & Salvador Cruz-Rambaud, 2019. "Internet of Things and Their Coming Perspectives: A Real Options Approach," Sustainability, MDPI, vol. 11(11), pages 1-15, June.
    18. Warren J. Hahn & James S. Dyer, 2011. "A Discrete Time Approach for Modeling Two-Factor Mean-Reverting Stochastic Processes," Decision Analysis, INFORMS, vol. 8(3), pages 220-232, September.
    19. B R Cobb & J M Charnes, 2010. "A graphical method for valuing switching options," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(11), pages 1596-1606, November.
    20. Weihan Li & Jin E. Zhang & Xinfeng Ruan & Pakorn Aschakulporn, 2024. "An empirical study on the early exercise premium of American options: Evidence from OEX and XEO options," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(7), pages 1117-1153, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jrpoli:v:80:y:2023:i:c:s0301420722007097. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/30467 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.