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Evaluating Natural Resource Investments under Different Model Dynamics: Managerial Insights

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  • Andrianos E. Tsekrekos
  • Mark B. Shackleton
  • RafaÅ‚ Wojakowski

Abstract

We focus on factors that drive the dynamics of commodity prices. We highlight the capital budgeting implications of three highly†cited, nested, multi†factor models for commodity prices that have been successful in empirical investigations. Competing assumptions regarding commodity prices and their convenience yields can account for differences close to 40% on average, and in excess of 60% in cases, in the valuation of typical natural resource investments. These value differences are found to increase with the maturity and the intrinsic value of the investment, and also with the level and the volatility of the resource's convenience yield. Resources such as oil or copper, that are used for production purposes, usually exhibit high and volatile convenience yields; thus our findings should be more relevant for decision†makers in such sectors.

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  • Andrianos E. Tsekrekos & Mark B. Shackleton & RafaÅ‚ Wojakowski, 2012. "Evaluating Natural Resource Investments under Different Model Dynamics: Managerial Insights," European Financial Management, European Financial Management Association, vol. 18(4), pages 543-575, September.
    • Handle: RePEc:bla:eufman:v:18:y:2012:i:4:p:543-575
    DOI: 10.1111/j.1468-036X.2010.00544.x
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    2. Sebastian Maier, 2021. "Re-evaluating natural resource investments under uncertainty: An alternative to limited traditional approaches," Annals of Operations Research, Springer, vol. 299(1), pages 907-937, April.
    3. Wenqing Zhang & Prasad Padmanabhan & Chia-Hsing Huang, 2015. "Sequential capital investment decision making under extreme cash fl ow situations: evidence using Monte Carlo simulation," Journal of Business Economics and Management, Taylor & Francis Journals, vol. 16(5), pages 877-900, October.
    4. Max F. Schöne & Stefan Spinler, 2017. "A four-factor stochastic volatility model of commodity prices," Review of Derivatives Research, Springer, vol. 20(2), pages 135-165, July.
    5. Savolainen, Jyrki, 2016. "Real options in metal mining project valuation: Review of literature," Resources Policy, Elsevier, vol. 50(C), pages 49-65.
    6. Abdullah Almansour and Margaret Insley, 2016. "The Impact of Stochastic Extraction Cost on the Value of an Exhaustible Resource: An Application to the Alberta Oil Sands," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    7. Cortazar, Gonzalo & Naranjo, Lorenzo & Sainz, Felipe, 2021. "Optimal decision policy for real options under general Markovian dynamics," European Journal of Operational Research, Elsevier, vol. 288(2), pages 634-647.
    8. 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.
    9. Roger Adkins & Dean Paxson, 2014. "Stochastic Equipment Capital Budgeting with Technological Progress," European Financial Management, European Financial Management Association, vol. 20(5), pages 1031-1049, November.

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