IDEAS home Printed from https://ideas.repec.org/a/eee/jrpoli/v52y2017icp296-307.html
   My bibliography  Save this article

Valuation of a hypothetical mining project under commodity price and exchange rate uncertainties by using numerical methods

Author

Listed:
  • Aminrostamkolaee, Behnam
  • Scroggs, Jeffrey S.
  • Borghei, Matin Sadat
  • Safdari-Vaighani, Ali
  • Mohammadi, Teymour
  • Hossein Pourkazemi, Mohammad

Abstract

One of the goals presented here is the use of a radial basis function (RBF) method to approximate the numerical values of a gold mining project. RBFs have many attractive features compared to implicit finite differences method (FDM) and explicit FDM. They are mesh-free, computationally more efficient in high dimensions, and very accurate. In other words, the model is more comprehensive, and results are more accurate compared to the previous works. This paper compares accuracy of the RBF method with that of the implicit method (FDM) in this case study. The results indicate that convergence order of the RBF is higher than that of the implicit method. Also, this paper compares the results of the RBF method with those of implicit method for various scenarios.

Suggested Citation

  • Aminrostamkolaee, Behnam & Scroggs, Jeffrey S. & Borghei, Matin Sadat & Safdari-Vaighani, Ali & Mohammadi, Teymour & Hossein Pourkazemi, Mohammad, 2017. "Valuation of a hypothetical mining project under commodity price and exchange rate uncertainties by using numerical methods," Resources Policy, Elsevier, vol. 52(C), pages 296-307.
    • Handle: RePEc:eee:jrpoli:v:52:y:2017:i:c:p:296-307
    DOI: 10.1016/j.resourpol.2017.04.004
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301420716304238
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.resourpol.2017.04.004?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. Haque, Md. Aminul & Topal, Erkan & Lilford, Eric, 2014. "A numerical study for a mining project using real options valuation under commodity price uncertainty," Resources Policy, Elsevier, vol. 39(C), pages 115-123.
    2. Lenos Trigeorgis, 1993. "Real Options and Interactions With Financial Flexibility," Financial Management, Financial Management Association, vol. 22(3), Fall.
    3. Merton, Robert C, 1987. "A Simple Model of Capital Market Equilibrium with Incomplete Information," Journal of Finance, American Finance Association, vol. 42(3), pages 483-510, July.
    4. Avinash K. Dixit & Robert S. Pindyck, 1994. "Investment under Uncertainty," Economics Books, Princeton University Press, edition 1, number 5474.
    5. Cortazar, Gonzalo & Casassus, Jaime, 1998. "Optimal Timing of a Mine Expansion: Implementing a Real Options Model," The Quarterly Review of Economics and Finance, Elsevier, vol. 38(3, Part 2), pages 755-769.
    6. Myers, Stewart C., 1977. "Determinants of corporate borrowing," Journal of Financial Economics, Elsevier, vol. 5(2), pages 147-175, November.
    7. Brennan, Michael J & Schwartz, Eduardo S, 1985. "Evaluating Natural Resource Investments," The Journal of Business, University of Chicago Press, vol. 58(2), pages 135-157, April.
    8. Costa Lima, Gabriel A. & Suslick, Saul B., 2006. "Estimating the volatility of mining projects considering price and operating cost uncertainties," Resources Policy, Elsevier, vol. 31(2), pages 86-94, June.
    9. 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.
    10. Shafiee, Shahriar & Topal, Erkan, 2010. "An overview of global gold market and gold price forecasting," Resources Policy, Elsevier, vol. 35(3), pages 178-189, September.
    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. Alameer, Zakaria & Elaziz, Mohamed Abd & Ewees, Ahmed A. & Ye, Haiwang & Jianhua, Zhang, 2019. "Forecasting gold price fluctuations using improved multilayer perceptron neural network and whale optimization algorithm," Resources Policy, Elsevier, vol. 61(C), pages 250-260.
    2. Ewees, Ahmed A. & Elaziz, Mohamed Abd & Alameer, Zakaria & Ye, Haiwang & Jianhua, Zhang, 2020. "Improving multilayer perceptron neural network using chaotic grasshopper optimization algorithm to forecast iron ore price volatility," Resources Policy, Elsevier, vol. 65(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. Haque, Md. Aminul & Topal, Erkan & Lilford, Eric, 2014. "A numerical study for a mining project using real options valuation under commodity price uncertainty," Resources Policy, Elsevier, vol. 39(C), pages 115-123.
    2. Savolainen, Jyrki, 2016. "Real options in metal mining project valuation: Review of literature," Resources Policy, Elsevier, vol. 50(C), pages 49-65.
    3. Garcia Fronti, Javier, 2015. "Modelo estocástico para la valuación de una inversión nanomédica [Nanomedical Stochastic Investment Valuation]," MPRA Paper 63948, University Library of Munich, Germany.
    4. 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.
    5. Lander, Diane M. & Pinches, George E., 1998. "Challenges to the Practical Implementation of Modeling and Valuing Real Options," The Quarterly Review of Economics and Finance, Elsevier, vol. 38(3, Part 2), pages 537-567.
    6. 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.
    7. Jan Vlachý, 2009. "Solving the Capacity Optimization Problem under Demand Uncertainty," Romanian Economic Journal, Department of International Business and Economics from the Academy of Economic Studies Bucharest, vol. 12(34), pages 97-116, (4).
    8. Anastasios Michailidis & Konstadinos Mattas, 2007. "Using Real Options Theory to Irrigation Dam Investment Analysis: An Application of Binomial Option Pricing Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 21(10), pages 1717-1733, October.
    9. 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.
    10. Collan, Mikael, 2004. "Giga-Investments: Modelling the Valuation of Very Large Industrial Real Investments," MPRA Paper 4328, University Library of Munich, Germany.
    11. Mohammad Rahman Ardhiansyah & Tsuyoshi Adachi & Junichiro Oda, 2023. "Stratified state aggregation (SSA) approach in real option valuation: combining price and grade uncertainties in tin mining projects," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 36(3), pages 371-381, September.
    12. Cheng, Cheng & Wang, Zhen & Liu, Mingming & Chen, Qiang & Gbatu, Abimelech Paye & Ren, Xiaohang, 2017. "Defer option valuation and optimal investment timing of solar photovoltaic projects under different electricity market systems and support schemes," Energy, Elsevier, vol. 127(C), pages 594-610.
    13. Cuypers, I.R.P., 2009. "Essays on equity joint ventures, uncertainty and experience," Other publications TiSEM 8dc79e86-c625-467f-a450-8, Tilburg University, School of Economics and Management.
    14. Marco Antonio Guimaraes Dias & Jose Paulo Teixeira, 2010. "Continuous-Time Option Games: Review of Models and Extensions," Multinational Finance Journal, Multinational Finance Journal, vol. 14(3-4), pages 219-254, September.
    15. Madlener, Reinhard & Stoverink, Simon, 2012. "Power plant investments in the Turkish electricity sector: A real options approach taking into account market liberalization," Applied Energy, Elsevier, vol. 97(C), pages 124-134.
    16. Twine, Edgar E. & Kiiza, Barnabas & Bashaasha, Bernard, 2015. "The Flexible Accelerator Model of Investment: An Application to Ugandan Tea- Processing Firms," African Journal of Agricultural and Resource Economics, African Association of Agricultural Economists, vol. 10(1), pages 1-15, March.
    17. Hunt, Richard A. & Song, Yue & Townsend, David M. & Stallkamp, Maximilian, 2021. "Internationalization of entrepreneurial firms: Leveraging real options reasoning through affordable loss logics," Journal of Business Research, Elsevier, vol. 133(C), pages 194-207.
    18. Caren Sureth, 2002. "Partially Irreversible Investment Decisions and Taxation under Uncertainty: A Real Option Approach," German Economic Review, Verein für Socialpolitik, vol. 3(2), pages 185-221, May.
    19. Armstrong, Margaret & Langrené, Nicolas & Petter, Renato & Chen, Wen & Petter, Carlos, 2019. "Accounting for tailings dam failures in the valuation of mining projects," Resources Policy, Elsevier, vol. 63(C), pages 1-1.
    20. Twine, Edgar E. & Omore, Amos & Githinji, Julius, 2018. "Uncertainty in milk production by smallholders in Tanzania and its implications for investment," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 21(1).

    More about this item

    Keywords

    Discounted cash flow; Real options valuation; Geometric Brownian Motion; Commodity price; Volatility; Implicit FDM and explicit FDM; Radial basis function; Exchange rate;
    All these keywords.

    JEL classification:

    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • Q3 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation
    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics

    Statistics

    Access and download statistics

    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:52:y:2017:i:c:p:296-307. 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.