Using common features to understand the behavior of metal-commodity prices and forecast them at different horizons

João Issler, Claudia Ferreira Rodrigues and Rafael Burjack

No 744, FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) from EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil)

Abstract: The objective of this article is to study (understand and forecast) spot metal price levels and changes at monthly, quarterly, and annual frequencies. Data consists of metal-commodity prices at a monthly and quarterly frequencies from 1957 to 2012, extracted from the IFS, and annual data, provided from 1900-2010 by the U.S. Geological Survey (USGS). We also employ the (relatively large) list of co-variates used in Welch and Goyal (2008) and in Hong and Yogo (2009). We investigate short- and long-run comovement by applying the techniques and the tests proposed in the common-feature literature. One of the main contributions of this paper is to understand the short-run dynamics of metal prices. We show theoretically that there must be a positive correlation between metal-price variation and industrial-production variation if metal supply is held fixed in the short run when demand is optimally chosen taking into account optimal production for the industrial sector. This is simply a consequence of the derived-demand model for cost-minimizing firms. Our empirical evidence fully supports this theoretical result, with overwhelming evidence that cycles in metal prices are synchronized with those in industrial production. This evidence is stronger regarding the global economy but holds as well for the U.S. economy to a lesser degree. Regarding out-of-sample forecasts, our main contribution is to show the benefits of forecast-combination techniques, which outperform individual-model forecasts - including the random-walk model. We use a variety of models (linear and non-linear, single equation and multivariate) and a variety of co-variates and functional forms to forecast the returns and prices of metal commodities. Using a large number of models (N large) and a large number of time periods (T large), we apply the techniques put forth by the common-feature literature on forecast combinations. Empirically, we show that models incorporating (short-run) common-cycle restrictions perform better than unrestricted models, with an important role for industrial production as a predictor for metal-price variation.

Date: 2013-08-22
New Economics Papers: this item is included in nep-agr and nep-for
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://repositorio.fgv.br/bitstreams/04fabd51-829 ... 7c632d5989b/download (application/pdf)

Related works:
Journal Article: Using common features to understand the behavior of metal-commodity prices and forecast them at different horizons (2014)
Working Paper: Using common features to understand the behavior of metal-commodity prices and forecast them at different horizons (2013)
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: https://EconPapers.repec.org/RePEc:fgv:epgewp:744

Access Statistics for this paper

More papers in FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) from EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil) Contact information at EDIRC.
Bibliographic data for series maintained by Núcleo de Computação da FGV EPGE ().