Abstract
Metal price, exchange rate, and operating costs are three of the most important sources of uncertainty in mining projects. In that sense, numerous research studies have been carried out to account for price uncertainty, while few others have incorporated the simultaneous effects of operating costs and price uncertainties. The purpose of this paper is to introduce the octanomial tree method to value an Australian gold mine project by adding three market uncertainties such as the gold spot price, USD/AUD exchange rate and the operative costs, under a multinomial tree approach. The proposed model combines the simplicity of the binomial tree model with the ability to deal efficiently with multiple uncertainties.
Highlights
Recent studies had shown that is often inappropriate to determine the value of a project through the traditional discounted cash flow (DCF) method (Trigeorgis, 1996; Copeland and Antikarov, 2001) since it does not include its operational flexibilities and future uncertainties
The purpose of this paper is to introduce the octanomial tree method to value an Australian gold mine project by adding three market uncertainties such as the gold spot price, USD/Australian Dollar (AUD) exchange rate and the operative costs, under a multinomial tree approach
Talking about natural resources investments, e.g., mining projects, some works had shown that the real options approach (ROA) approach constitutes a better tool for assessing investment projects under uncertain market and operational conditions, which characterizes these projects, compared to DCF methods, such as the net present value (NPV)
Summary
Recent studies had shown that is often inappropriate to determine the value of a project through the traditional discounted cash flow (DCF) method (Trigeorgis, 1996; Copeland and Antikarov, 2001) since it does not include its operational flexibilities and future uncertainties. Brennan and Schwartz (1985) were the ones that developed, for the first time, a stochastic model to value mining projects, a copper mine, where they assumed that the commodity price follows a GBM They extended this approach by introducing stochastic control theory to find optimal exercise policies. Under these different frameworks, Dehghani, Ataee-pour and Esfahanipour (2014) developed a novel valuation method named pyramid technique based on the multidimensional binomial tree method as an extension of Clewlow and Strickland (1998) model Under this model, the authors evaluated a copper mine with two simultaneous stochastic processes, metal prices and operating costs.
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