@article{9e6c42db08ff4b97a58eb424a00cea8c,
title = "Extreme price co-movement of commodity futures and industrial production growth: an empirical evaluation",
abstract = "This paper studies how the extreme price co-movement of commodity futures indicates industrial production (IP) growth. In this regard, we model synchronized movements and large price changes into one measure by characterizing upside and downside price extremes. We find that the derived price extremes are positively associated with IP growth over the next quarter. We further conclude that such impact is not symmetric, as the impact led by downside extremes is robust whereas that of upside extremes is not. Our results reinforce the informational friction theory as well as those financial studies that emphasize downside risk.",
keywords = "Commodity futures, Extreme price co-movement, GAS-factor copula, Industrial production growth, Panel regressions",
author = "Xiaoqian Wen and Yuxin Xie and Pantelous, \{Athanasios A.\}",
note = "Funding Information: We have benefited from comments and suggestions from Michael Brennan, Yaomin Chiang, Phil Dybvig, Ana-Maria Fuertes, Neil Kellard, Lutz Kilian, Yu Li, Marcel Prokopczuk, George Skiadopoulos, Michael Sockin, Yajun Wang, Wei Xiong and seminar participants at the 4th Symposium on Quantitative Finance and Risk Analysis (QFRA 2018), and workshops at the Southwestern University of Finance and Economics, National Taiwan University, and Monash Business School. We thank Dong Hwan Oh of the Federal Reserve Board for help with the Matlab code. We gratefully acknowledge financial support from the NSFC fund (project number 71601157 and 7180030687 ) and the Fundamental Research Funds for the Central Universities of the Southwestern University of Finance and Economics (No. JBK 1805003 ). Funding Information: We have benefited from comments and suggestions from Michael Brennan, Yaomin Chiang, Phil Dybvig, Ana-Maria Fuertes, Neil Kellard, Lutz Kilian, Yu Li, Marcel Prokopczuk, George Skiadopoulos, Michael Sockin, Yajun Wang, Wei Xiong and seminar participants at the 4th Symposium on Quantitative Finance and Risk Analysis (QFRA 2018), and workshops at the Southwestern University of Finance and Economics, National Taiwan University, and Monash Business School. We thank Dong Hwan Oh of the Federal Reserve Board for help with the Matlab code. We gratefully acknowledge financial support from the NSFC fund (project number 71601157 and 7180030687) and the Fundamental Research Funds for the Central Universities of the Southwestern University of Finance and Economics (No. JBK 1805003). Publisher Copyright: {\textcopyright} 2022 Elsevier B.V.",
year = "2022",
month = apr,
doi = "10.1016/j.eneco.2022.105915",
language = "English",
volume = "108",
journal = "Energy Economics",
issn = "0140-9883",
publisher = "Elsevier BV",
}