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Estimating copper concentrates benchmark prices under dynamic market conditions

Author

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  • Díaz-Borrego, Francisco J.
  • Escobar-Peréz, Bernabé
  • Miras-Rodríguez, María del Mar

Abstract

Copper concentrates are the primary product sold by copper mines to traders or smelters. Their price is set in private agreements following unofficial market practices which, along with the fact of the wide variety of concentrates layouts traded worldwide, make problematic for any market participant to have a clear price reference for a specific concentrate. This paper presents a copper concentrates benchmark price model which provides suitable short-term price estimations based on metals and discounts forecasts, as well as on copper, gold and silver spot and future prices data from the LME and COMEX. The model, which redeems considerably low forecast error values for the short-term concentrate prices, constitutes a useful and applicable tool for miners, traders and smelters to set a benchmark price level for their copper concentrate transactions, also helping them optimize their operations, as well as estimate their immediate liquidity needs or their actual necessity to hedge the price risks associated to their concentrate trading. In addition, different concentrates layouts have been analyzed to test the model's behavior with the most common specification and blends of copper concentrates demanded by the market, as well as to portray the model's forecasting capacity and its ability to convey information on the future relevance of the different components of pricing in the most frequent timeframe in which copper concentrate trading takes place.

Suggested Citation

  • Díaz-Borrego, Francisco J. & Escobar-Peréz, Bernabé & Miras-Rodríguez, María del Mar, 2021. "Estimating copper concentrates benchmark prices under dynamic market conditions," Resources Policy, Elsevier, vol. 70(C).
    • Handle: RePEc:eee:jrpoli:v:70:y:2021:i:c:s0301420720309880
    DOI: 10.1016/j.resourpol.2020.101959
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    References listed on IDEAS

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    1. Nabavi, Zohre & Mirzehi, Mohammad & Dehghani, Hesam, 2024. "Reliable novel hybrid extreme gradient boosting for forecasting copper prices using meta-heuristic algorithms: A thirty-year analysis," Resources Policy, Elsevier, vol. 90(C).

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