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Common factors and the dynamics of industrial metal prices. A forecasting perspective

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  • Kwas, Marek
  • Paccagnini, Alessia
  • Rubaszek, Michał

Abstract

This study aims to analyze the suitability of factor models in describing the dynamics of real prices for four main non-ferrous industrial metals: aluminium, copper, nickel and zinc. For that purpose, using an extensive dataset of monthly time series covering the years 1980–2019, we extract four different common factors explaining commodity prices, exchange rates, financial and macroeconomic indicators. Next, we examine these factors as potential predictors of the movements of four metal prices with the use of two model classes: direct forecasts (DF) and factor augmented vector autoregressions (VAR). We show that for three out of four metals (aluminium, nickel and zinc) VAR models provide relatively good point and density forecasts, outperforming the random walk benchmark as well as DF models.

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  • Kwas, Marek & Paccagnini, Alessia & Rubaszek, Michał, 2021. "Common factors and the dynamics of industrial metal prices. A forecasting perspective," Resources Policy, Elsevier, vol. 74(C).
    • Handle: RePEc:eee:jrpoli:v:74:y:2021:i:c:s0301420721003299
    DOI: 10.1016/j.resourpol.2021.102319
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    More about this item

    Keywords

    Industrial industrial metal prices; Forecasting; Factor models; Autoregressive models;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • Q11 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Aggregate Supply and Demand Analysis; Prices

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