Macroeconomic forecasts and commodity futures volatility

Wuyi Ye, Ranran Guo, Bruno Deschamps, Ying Jiang and Xiaoquan Liu

Economic Modelling, 2021, vol. 94, issue C, 981-994

Abstract: We examine the impact of macroeconomic expectations on the volatility of Chinese commodity futures. As commodity futures are forward-looking, we expect them to be influenced by market expectations of the future economic situation, which we capture using a data set of professional macroeconomic forecasts. We analyze 15 commodity futures contracts using a GARCH-MIDAS model that contains daily price volatility and monthly macroeconomic forecasts. We find that the volatility of commodity futures is impacted more strongly by macroeconomic forecasts than by concurrent economic conditions. Furthermore, augmenting the volatility model with the macroeconomic forecasts improves the model ability to predict future volatility. These volatility predictions also offer economic gains to a mean-variance utility investor in a portfolio setting. Finally, the impact of macroeconomic forecasts is dependent on the state of the economy.

Keywords: Commodity futures; Volatility; GARCH-MIDAS model; Macroeconomic forecasts (search for similar items in EconPapers)
JEL-codes: E44 G13 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0264999319312088
Full text for ScienceDirect subscribers only

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: https://EconPapers.repec.org/RePEc:eee:ecmode:v:94:y:2021:i:c:p:981-994

DOI: 10.1016/j.econmod.2020.02.038

Access Statistics for this article

Economic Modelling is currently edited by S. Hall and P. Pauly

More articles in Economic Modelling from Elsevier
Bibliographic data for series maintained by Catherine Liu ().