Economics at your fingertips  

Regime-dependent commodity price dynamics: A predictive analysis

Jesus Crespo-Cuaresma, Ines Fortin, Jaroslava Hlouskova () and Michael Obersteiner
Additional contact information
Jesus Crespo-Cuaresma: 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
Ines Fortin: Institute for Advanced Studies, Vienna, Austria
Michael Obersteiner: University of Oxford, Oxford, UK, and International Institute of Applied Systems Analysis (IIASA), Laxenburg, Austria

Authors registered in the RePEc Author Service: Jesus Crespo Cuaresma ()

No 28, IHS Working Paper Series from Institute for Advanced Studies

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.

Keywords: Commodity prices; forecasting; threshold models; forecast performance; states of economy (search for similar items in EconPapers)
JEL-codes: C53 F47 Q02 (search for similar items in EconPapers)
Pages: 50 pages
Date: 2021-01
New Economics Papers: this item is included in nep-for
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link) First version, 2021 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

Ordering information: This working paper can be ordered from
Institute for Advanced Studies - Library, Josefstädterstr. 39, A-1080 Vienna, Austria

Access Statistics for this paper

More papers in IHS Working Paper Series from Institute for Advanced Studies Josefstädterstr. 39, A-1080 Vienna, Austria. Contact information at EDIRC.
Bibliographic data for series maintained by Doris Szoncsitz ().

Page updated 2022-10-03
Handle: RePEc:ihs:ihswps:28