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Published in: Mathematics and Financial Economics 4/2015

01-10-2015

Modeling and estimating commodity prices: copper prices

Authors: Roger J.-B. Wets, Ignacio Rios

Published in: Mathematics and Financial Economics | Issue 4/2015

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Abstract

A new methodology is laid out for the modeling of commodity prices, it departs from the ‘standard’ approach in that it makes a definite distinction between the analysis of the short term and long term regimes. In particular, this allows us to come up with an explicit drift term for the short-term process whereas the long-term process is primarily driftless due to inherent high volatility of commodity prices excluding an almost negligible mean reversion term. Not unexpectedly, the information used to build the short-term process relies on more than just historical prices but takes into account additional information about the state of the market. This work is done in the context of copper prices but a similar approach should be applicable to wide variety of commodities although certainly not all since commodities come with very distinct characteristics. In addition, our model also takes into account inflation which leads us to consider a multi-dimensional system for which one can generate explicit solutions.

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Appendix
Available only for authorised users
Footnotes
1
The inclusion or not of a mean reversion term in the long-term process will be taken up in the section devoted to the long-term process.
 
2
How futures’ prices are determined is not of immediate concern including the role played by any of the factors mentioned above; one could consult [5, 8] for an analysis of how they might depend on stock levels and spot prices associated with contracts involving actual deliveries.
 
3
In the Pilipovic model, prices are modeled by a system of two stochastic differential equations: the first one for the spot price, which is assumed to mean-revert toward the equilibrium price level, and the second for the equilibrium price level, which is supposed to follow a log-gaussian distribution,
$$\begin{aligned} dS_t&= \alpha \left( L_t - S_t\right) dt + \sigma S_t dw_t\\ dL_t&=\mu L_t dt + L_t yi dz_t \end{aligned}$$
 
4
We also implemented the Phillips–Perron test but the results obtained were the same as for the ADF test.
 
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Metadata
Title
Modeling and estimating commodity prices: copper prices
Authors
Roger J.-B. Wets
Ignacio Rios
Publication date
01-10-2015
Publisher
Springer Berlin Heidelberg
Published in
Mathematics and Financial Economics / Issue 4/2015
Print ISSN: 1862-9679
Electronic ISSN: 1862-9660
DOI
https://doi.org/10.1007/s11579-014-0140-2