Incorporating stochastic correlations into mining project evaluation using the Jacobi process

Aldin Ardian and Mustafa Kumral

Resources Policy, 2020, vol. 65, issue C

Abstract: Uncertainty is an important phenomenon in mine project evaluation. Recovery, grade, commodity price, discount rate, and operating costs are highly uncertain variables. Given that uncertainties cannot be fully eliminated, mining companies focus on assessing risks associated with uncertainties. Mining projects generally encompass 10–50 years, and the evolution of uncertain parameters over this long time period is also uncertain. Since the future cannot be predicted, one way to deal with uncertainty is to create probable images of reality through simulation. When simulating multiple uncertain variables over time, an immediate problem is how to handle correlations among uncertain variables because the correlations themselves are uncertain variables. In this paper, the Jacobi process is used to treat the correlations stochastically. A case study was implemented in a mine project evaluation (e.g., net present value and option pricing), in which the gold prices and the US interest rates were considered as correlated uncertain variables. The correlations among uncertain variables significantly affected the value of the mining project. The Jacobi process can be used as a tool to increase the performance of mine project evaluation.

Keywords: Correlation; Jacobi process; Mineral industries; Mine project evaluation; Risk assessment; Stochastic process (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0301420719306191
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:jrpoli:v:65:y:2020:i:c:s0301420719306191

DOI: 10.1016/j.resourpol.2019.101558

Access Statistics for this article

Resources Policy is currently edited by R. G. Eggert

More articles in Resources Policy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().