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Can oil prices help estimate commodity futures prices? The cases of copper and silver


  • Cortazar, Gonzalo
  • Eterovic, Francisco


There is an extensive literature on modeling the stochastic process of commodity futures. It has been shown that models with several risk factors are able to adequately fit both the level and the volatility structure of observed transactions with reasonable low errors. One of the characteristics of commodity futures markets is the relatively short term maturity of their contracts, typically ranging for only a few years. This poses a problem for valuing long term investments that require extrapolating the observed term structure. There has been little work on how to effectively do this extrapolation and in measuring its errors. (Cortazar et al., 2008a) and (Cortazar et al., 2008b) propose a multicommodity model that jointly estimates two commodities, one with much longer maturity futures contracts than the other, showing that futures prices of one commodity may be useful information for estimating the stochastic process of another. They implement the procedure using highly correlated commodities like WTI and Brent. In this paper we analyze using prices of long term oil futures contracts to help estimate long term copper and silver future prices. We start by analyzing the performance of the (Cortazar et al., 2008a) and (Cortazar et al., 2008b) multicommodity model, now applied to oil-copper and oil-silver which have much lower correlation than the WTI-Brent contracts. We show that for these commodities with lower correlation the multicommodity model seems not to be effective. We then propose a modified multicommodity model with a much simpler structure which is easier to estimate and that uses the non-stationary long term process of oil to help estimate long term copper and silver futures prices, achieving a much better fit than using available individual or multicommodity models.

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  • Cortazar, Gonzalo & Eterovic, Francisco, 2010. "Can oil prices help estimate commodity futures prices? The cases of copper and silver," Resources Policy, Elsevier, vol. 35(4), pages 283-291, December.
  • Handle: RePEc:eee:jrpoli:v:35:y:2010:i:4:p:283-291

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    References listed on IDEAS

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    Cited by:

    1. Buhl, Hans Ulrich & Strauß, Sofie & Wiesent, Julia, 2011. "The impact of commodity price risk management on the profits of a company," Resources Policy, Elsevier, vol. 36(4), pages 346-353.
    2. Sánchez Lasheras, Fernando & de Cos Juez, Francisco Javier & Suárez Sánchez, Ana & Krzemień, Alicja & Riesgo Fernández, Pedro, 2015. "Forecasting the COMEX copper spot price by means of neural networks and ARIMA models," Resources Policy, Elsevier, vol. 45(C), pages 37-43.
    3. Gonzalo Cortazar & Eduardo S. Schwartz & Claudio Tapia, 2012. "Credit Spreads in Illiquid Markets: Model and Implementation," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 48(6), pages 53-72, November.
    4. Cortazar, Gonzalo & Kovacevic, Ivo & Schwartz, Eduardo S., 2015. "Expected commodity returns and pricing models," Energy Economics, Elsevier, vol. 49(C), pages 60-71.
    5. Abdullah Almansour and Margaret Insley, 2016. "The Impact of Stochastic Extraction Cost on the Value of an Exhaustible Resource: An Application to the Alberta Oil Sands," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    6. Gonzalo Cortazar & Cristobal Millard & Hector Ortega & Eduardo S. Schwartz, 2016. "Commodity Price Forecasts, Futures Prices and Pricing Models," NBER Working Papers 22991, National Bureau of Economic Research, Inc.
    7. Gonzalo Cortazar & Simon Gutierrez & Hector Ortega, 2016. "Empirical Performance of Commodity Pricing Models: When is it Worthwhile to Use a Stochastic Volatility Specification?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 36(5), pages 457-487, May.
    8. Gonzalo Cortazar & Eduardo S. Schwartz & Claudio Tapia, 2012. "Credit Spreads in Illiquid Markets: Model and Implementation," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 48(6), pages 53-72, November.


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