Risk and uncertainty are attached to mining projects, and making decisions, hedging, future investment and evaluation of mining projects depend on forecasting the future price. The future technologic developments in mining will be primarily influenced by the future commodity prices. A few approaches, with different confidences are proposed to predict price movement in the future. This research introduces a new comprehensive version of the mean reverting jump diffusion model for natural-resource commodity prices. The novel model proposes that the historical data of mineral commodities have three terms to demonstrate fluctuation of prices: mean reversion component, diffusion component and jump component. The model calculates each term individually to compute the future prices of mineral commodities._x000D_
Subsequently, in the second section of the paper, the model is implemented for monthly historical data of gold price from January 1968 to May 2008. This research is investigating the relationship between the historical oil price and inflation with the gold price. This is followed by a future estimation of gold price fluctuations up to 2018. The results from the application of this new method are discussed in the context of how they accurately replicate the historical gold price and how they can predict the future gold price._x000D_
FORMAL CITATION:Shafiee, S and Topal, E, 2008. Introducing a new model to forecast mineral commodity price, in Proceedings First International Future Mining Conference and Exhibition 2008, pp 243-250 (The Australasian Institute of Mining and Metallurgy: Melbourne).