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Mean-reversion, non-linearities and the dynamics of industrial metal prices. A forecasting perspective

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  • Rubaszek, Michał
  • Karolak, Zuzanna
  • Kwas, Marek

Abstract

We analyse the dynamics of real prices for main non-ferrous industrial metals: aluminium, copper, nickel and zinc. The estimates based on monthly data from 1980 to 2019 show that the prices are mean reverting and the pace of mean reversion is regime dependent. The results of the out-of-sample forecasting competition provide ample evidence that mean-reverting models deliver significantly better forecasts than the naive random walk. However, allowing for non-linearity by introducing threshold structure does not lead to further improvement in the quality of forecasts.

Suggested Citation

  • Rubaszek, Michał & Karolak, Zuzanna & Kwas, Marek, 2020. "Mean-reversion, non-linearities and the dynamics of industrial metal prices. A forecasting perspective," Resources Policy, Elsevier, vol. 65(C).
  • Handle: RePEc:eee:jrpoli:v:65:y:2020:i:c:s0301420719305379
    DOI: 10.1016/j.resourpol.2019.101538
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    More about this item

    Keywords

    Industrial metal prices; Forecasting; Autoregressive models; Threshold models;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • Q31 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - Demand and Supply; Prices

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