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Investigating the effect of price process selection on the value of a metal mining asset portfolio

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Listed:
  • Mikael Collan

    (Lappeenranta University of Technology)

  • Jyrki Savolainen

    (Lappeenranta University of Technology)

  • Pasi Luukka

    (Lappeenranta University of Technology)

Abstract

This paper studies how the selection of the metal price process used and the choice of selected other modeling assumptions affect the value of a metal mining company’s mining asset portfolio. We compare results from when metal prices are assumed to be independent of each other, correlated with each other, and correlated with an external factor. These studies are carried out by using the geometric Brownian motion-based and mean-reverting metal price processes. What is also studied is the effect caused by replacing one of the portfolio metals with a typically counter cyclic metal, in this case gold. Numerical simulation analysis is made to study these issues. The results highlight the importance of correctly selecting the price processes used and corroborate some earlier findings on the topic, while also highlighting the effects of process and other modeling choices on (real) option valuation.

Suggested Citation

  • Mikael Collan & Jyrki Savolainen & Pasi Luukka, 2017. "Investigating the effect of price process selection on the value of a metal mining asset portfolio," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 30(2), pages 107-115, July.
  • Handle: RePEc:spr:minecn:v:30:y:2017:i:2:d:10.1007_s13563-017-0102-2
    DOI: 10.1007/s13563-017-0102-2
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    1. Achille N. Njike & Mustafa Kumral, 2019. "Mining corporate portfolio optimization model with company’s operational performance level and international risk," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 32(3), pages 307-315, November.

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    More about this item

    Keywords

    Metal mining; Price process choice; gBm; Mean-reverting process; Simulation;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • Q31 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - Demand and Supply; Prices

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