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Regime-dependent commodity price dynamics: A predictive analysis

Author

Listed:
  • Crespo-Cuaresma, Jesus

    (Vienna University of Economics and Business, Vienna, International Institute of Applied Systems Analysis (IIASA), Laxenburg, Wittgenstein Center for Demography and Global Human Capital, and Austrian Institute of Economic Research (WIFO), Vienna, Austria)

  • Fortin, Ines

    (Institute for Advanced Studies, Vienna, Austria)

  • Hlouskova, Jaroslava

    (Institute for Advanced Studies, Vienna, Austria, International Institute of Applied Systems Analysis (IIASA), Laxenburg, Austria, and University of Economics in Bratislava, Slovakia)

  • Obersteiner, Michael

    (University of Oxford, Oxford, UK, and International Institute of Applied Systems Analysis (IIASA), Laxenburg, Austria)

Abstract
We develop an econometric modelling framework to forecast commodity prices taking into account potentially different dynamics and linkages existing at different states of the world and using different performance measures to validate the predictions. We assess the extent to which the quality of the forecasts can be improved by entertaining different regime-dependent threshold models considering different threshold variables. We evaluate prediction quality using both loss minimization and profit maximization measures based on directional accuracy, directional value, the ability to predict adverse movements and returns implied by a trading strategy. Our analysis provides overwhelming evidence that allowing for regime-dependent dynamics leads to improvements in predictive ability for the Goldman Sachs Commodity Index, as well as for its five sub-indices (energy, industrial metals, precious metals, agriculture, livestock). Our results suggest the existence of a trade-off between predictive ability based on loss and profit measures, which implies that the particular aim of the prediction exercise carried out plays a very important role in terms of defining which set of models is the best to use.

Suggested Citation

  • Crespo-Cuaresma, Jesus & Fortin, Ines & Hlouskova, Jaroslava & Obersteiner, Michael, 2021. "Regime-dependent commodity price dynamics: A predictive analysis," IHS Working Paper Series 28, Institute for Advanced Studies.
    • Handle: RePEc:ihs:ihswps:28
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    File URL: https://irihs.ihs.ac.at/id/eprint/5600/
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Commodity prices; forecasting; threshold models; forecast performance; states of economy;
    All these keywords.

    JEL classification:

    • Q02 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Commodity Market
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • F47 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Forecasting and Simulation: Models and Applications

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