EconPapers    
Economics at your fingertips  
 

Forecasting commodity prices out-of-sample: Can technical indicators help?

Yudong Wang, Li Liu and Chongfeng Wu

International Journal of Forecasting, 2020, vol. 36, issue 2, 666-683

Abstract: Economic variables are often used for forecasting commodity prices, but technical indicators have received much less attention in the literature. This paper demonstrates the predictability of commodity price changes using many technical indicators. Technical indicators are stronger predictors than economic indicators, and their forecasting performances are not affected by the problems of data mining or time changes. An investor with mean–variance preference receives utility gains of between 104.4 and 185.5 basis points from using technical indicators. Further analysis shows that technical indicators also perform better than economic variables for forecasting the density of commodity price changes.

Keywords: Forecasting; Commodity price; Technical indicators; Predictive regression; Forecast combination (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1) Track citations by RSS feed

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0169207019302286
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:intfor:v:36:y:2020:i:2:p:666-683

DOI: 10.1016/j.ijforecast.2019.08.004

Access Statistics for this article

International Journal of Forecasting is currently edited by R. J. Hyndman

More articles in International Journal of Forecasting from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2021-09-14
Handle: RePEc:eee:intfor:v:36:y:2020:i:2:p:666-683