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Forecasting prices of selected metals with Bayesian data-rich models

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  • Drachal, Krzysztof

Abstract

The paper presents application of various Bayesian model combination schemes to metals spot prices forecasting. The considered schemes arise from recently gaining attention Dynamic Model Averaging (DMA). Lead, nickel and zinc spot prices are analyzed. Monthly data from 1996 to 2017 are used. The considered schemes seem to be an interesting alternative to some benchmark models. Interestingly, model selection is found more beneficial to tightening forecast accuracy than model averaging.

Suggested Citation

  • Drachal, Krzysztof, 2019. "Forecasting prices of selected metals with Bayesian data-rich models," Resources Policy, Elsevier, vol. 64(C).
    • Handle: RePEc:eee:jrpoli:v:64:y:2019:i:c:s0301420719306713
    DOI: 10.1016/j.resourpol.2019.101528
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