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Digital Library of the
European Council for Modelling and Simulation |
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Title: |
Commodities Prices Modeling Using Gaussian Poisson-Exponential Stochastic Processes, A Practical Implementation In The Case Of Copper |
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Authors: |
Mariano Mendez Suarez, Prosper Lamothe Fernandez |
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Published in:
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(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: 978-0-9553018-8-9 23rd
European Conference on Modelling and Simulation, Madrid, June
9-12, 2009 |
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Citation
format: |
Suarez, M. M., & Lamothe Fernandez, P. (2009). Commodities Prices Modeling
Using Gaussian Poisson-Exponential 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. 433-438). European Council for
Modeling and Simulation. doi:10.7148/2009-0433-0438 |
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DOI: |
http://dx.doi.org/10.7148/2009-0433-0438 |
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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 projects’ 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. |
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