文献类型：期刊文献

英文题名：Early warning model based on correlated networks in global crude oil markets

作者：Yu, Jia-Wei[1];Xie, Wen-Jie[1,2];Jiang, Zhi-Qiang[1,2]

机构：[1]East China Univ Sci & Technol, Dept Finance, 130 Meilong Rd,POB 114, Shanghai 200237, Peoples R China;[2]East China Univ Sci & Technol, Res Ctr Econophys, Shanghai 200237, Peoples R China

年份：2018

卷号：490

起止页码：1335

外文期刊名：PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS

收录：;EI(收录号：20173804192306);WOS:【SSCI(收录号:WOS:000415912900117)，SCI-EXPANDED(收录号:WOS:000415912900117)】；

基金：This work was partially supported by the National Natural Science Foundation of China (11075054 and 71571121), Shanghai 'Chen Guang' Project (2012CG34), and the Fundamental Research Funds for the Central Universities (222201718006).

语种：英文

外文关键词：Systemic risk; Early warning model; Network density; Modularity

摘要：Applying network tools on predicting and warning the systemic risks provides a novel avenue to manage risks in financial markets. Here, we construct a series of global crude oil correlated networks based on the historical 57 oil prices covering a period from 1993 to 2012. Two systemic risk indicators are constructed based on the density and modularity of correlated networks. The local maximums of the risk indicators are found to have the ability to predict the trends of oil prices. In our sample periods, the indicator based on the network density sends five signals and the indicator based on the modularity index sends four signals. The four signals sent by both indicators are able to warn the drop of future oil prices and the signal only sent by the network density is followed by a huge rise of oil prices. Our results deepen the application of network measures on building early warning models of systemic risks and can be applied to predict the trends of future prices in financial markets. (C) 2017 Elsevier B.V. All rights reserved.