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 of the 24 cases.

Authors

Publication Details

Journal
The North American Journal of Economics and Finance
Published
2024-11-28
DOI
https://doi.org/10.1016/j.najef.2024.102309
Citations
3
Primary Topic
Market Dynamics and Volatility
Type
article
Field-Weighted Citation Impact
3.39

Funders

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article

Factors of predictive power for metal commodities

Patric Papenfuß, Andreas Rathgeber, Amelie Schischke
3 citations
The North American Journal of Economics and Finance
Market Dynamics and Volatility
3.39
article

Factors of predictive power for metal commodities

Patric Papenfuß, Andreas Rathgeber, Amelie Schischke
article en
3 citations

Abstract

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 of the 24 cases.

The North American Journal of Economics and FinanceVol. 76
World Bank Group, Israel Science Foundation, Bundesministerium für Wirtschaft und Energie
Openalex Percentile: Top 6%
Market Dynamics and Volatility
3.39
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Factors of predictive power for metal commodities — Patric Papenfuß, Andreas Rathgeber, et al. · The North American Journal of Economics and Finance (2024) | TGRS Research Map | TGRS