
Digital Library of the
European Council for Modelling and Simulation 
Title: 
Commodities Prices Modeling Using Gaussian PoissonExponential Stochastic Processes, A Practical Implementation In The Case Of Copper 
Authors: 
Mariano Mendez Suarez, Prosper Lamothe Fernandez 
Published in: 
(2009).ECMS
2009 Proceedings edited by J. Otamendi, A. Bargiela, J. L. Montes, L. M. Doncel
Pedrera. European Council for Modeling and
Simulation. doi:10.7148/2009 ISBN: 9780955301889 23^{rd}
European Conference on Modelling and Simulation, Madrid, June
912, 2009 
Citation
format: 
Suarez, M. M., & Lamothe Fernandez, P. (2009). Commodities Prices Modeling
Using Gaussian PoissonExponential Stochastic Processes, A Practical
Implementation In The Case Of Copper. ECMS 2009 Proceedings edited by J. Otamendi, A. Bargiela, J. L.
Montes, L. M. Doncel Pedrera (pp. 433438). European Council for
Modeling and Simulation. doi:10.7148/200904330438 
DOI: 
http://dx.doi.org/10.7148/200904330438 
Abstract: 
Due
to an assignment, received from a Chilean mining company, to value a copper
mine with an estimated life span of several decades, we implemented a model
of copper prices using mean reversion with Gaussian Poisson exponential
jumps. The
parameters of the model are extracted from the copper prices series. The
exponential distributions of the jumps are estimated via a standard
simulation program using best likelihood methods. Until the model was implemented,
the company had been using a long term mean price to
estimate mining projectsâ€™ cash flows. This approach had worked satisfactorily
given that, as shown in the Chart 1, the average price of copper had ranged
around 100 cents of USD per pound between 1996 and 2004. 
Full
text: 