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Factors of predictive power for metal commodities

  • There are numerous forecasting studies on commodity prices using various micro- and macroeconomic indicator sets. However, commodity markets have undergone a substantial transformation in the last 20 years, with periods of the financialization, and possibly also a de-financialization, which should also be reflected in the commodity price forecasts. To identify the changes in price predictors and determinants, we individually forecast 24 metal prices one-month ahead in the pre- and post financial crisis period, where we identify the autoregressive price components having a large impact across all commodities and periods. However, interest rates are of larger impact in the first sub-sample, whereas commodity- and financial market indices are dominating in the second sub-sample. Further, we perform an out-of-sample forecast over the entire timespan, where we are able to significantly outperform the predefined benchmark forecast models, a random-walk and a random-walk with drift, in 12 ofThere are numerous forecasting studies on commodity prices using various micro- and macroeconomic indicator sets. However, commodity markets have undergone a substantial transformation in the last 20 years, with periods of the financialization, and possibly also a de-financialization, which should also be reflected in the commodity price forecasts. To identify the changes in price predictors and determinants, we individually forecast 24 metal prices one-month ahead in the pre- and post financial crisis period, where we identify the autoregressive price components having a large impact across all commodities and periods. However, interest rates are of larger impact in the first sub-sample, whereas commodity- and financial market indices are dominating in the second sub-sample. Further, we perform an out-of-sample forecast over the entire timespan, where we are able to significantly outperform the predefined benchmark forecast models, a random-walk and a random-walk with drift, in 12 of the 24 cases.show moreshow less

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Metadaten
Author:Patric PapenfußGND, Amelie SchischkeGND, Andreas RathgeberORCiDGND
URN:urn:nbn:de:bvb:384-opus4-1173472
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/117347
ISSN:1062-9408OPAC
Parent Title (English):The North American Journal of Economics and Finance
Publisher:Elsevier BV
Place of publication:Amsterdam
Type:Article
Language:English
Year of first Publication:2025
Publishing Institution:Universität Augsburg
Release Date:2024/12/06
Volume:76
First Page:102309
DOI:https://doi.org/10.1016/j.najef.2024.102309
Institutes:Mathematisch-Naturwissenschaftlich-Technische Fakultät
Mathematisch-Naturwissenschaftlich-Technische Fakultät / Institut für Materials Resource Management
Mathematisch-Naturwissenschaftlich-Technische Fakultät / Institut für Materials Resource Management / Professur für Applied Data Analysis
Nachhaltigkeitsziele
Nachhaltigkeitsziele / Ziel 10 - Weniger Ungleichheiten
Dewey Decimal Classification:5 Naturwissenschaften und Mathematik / 50 Naturwissenschaften / 500 Naturwissenschaften und Mathematik
Licence (German):CC-BY 4.0: Creative Commons: Namensnennung (mit Print on Demand)