{"title":"动态行业不确定性网络与商业周期","authors":"Jozef Baruník, Mattia Bevilacqua, R. Faff","doi":"10.2139/ssrn.3768370","DOIUrl":null,"url":null,"abstract":"We argue that uncertainty network structures extracted from option prices contain valuable information for business cycles. Classifying U.S. industries according to their contribution to system-related uncertainty across business cycles, we uncover an uncertainty hub role for the communications, industrials and information technology sectors, while shocks to materials, real estate and utilities do not create strong linkages in the network. Moreover, we find that this ex-ante network of uncertainty is a useful predictor of business cycles, especially when it is based on uncertainty hubs. The industry uncertainty network behaves counter-cyclically in that a tighter network tends to associate with future business cycle contractions.","PeriodicalId":379040,"journal":{"name":"ERN: Business Cycles (Topic)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Dynamic Industry Uncertainty Networks and the Business Cycle\",\"authors\":\"Jozef Baruník, Mattia Bevilacqua, R. Faff\",\"doi\":\"10.2139/ssrn.3768370\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We argue that uncertainty network structures extracted from option prices contain valuable information for business cycles. Classifying U.S. industries according to their contribution to system-related uncertainty across business cycles, we uncover an uncertainty hub role for the communications, industrials and information technology sectors, while shocks to materials, real estate and utilities do not create strong linkages in the network. Moreover, we find that this ex-ante network of uncertainty is a useful predictor of business cycles, especially when it is based on uncertainty hubs. The industry uncertainty network behaves counter-cyclically in that a tighter network tends to associate with future business cycle contractions.\",\"PeriodicalId\":379040,\"journal\":{\"name\":\"ERN: Business Cycles (Topic)\",\"volume\":\"102 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-01-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ERN: Business Cycles (Topic)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.3768370\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ERN: Business Cycles (Topic)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3768370","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Dynamic Industry Uncertainty Networks and the Business Cycle
We argue that uncertainty network structures extracted from option prices contain valuable information for business cycles. Classifying U.S. industries according to their contribution to system-related uncertainty across business cycles, we uncover an uncertainty hub role for the communications, industrials and information technology sectors, while shocks to materials, real estate and utilities do not create strong linkages in the network. Moreover, we find that this ex-ante network of uncertainty is a useful predictor of business cycles, especially when it is based on uncertainty hubs. The industry uncertainty network behaves counter-cyclically in that a tighter network tends to associate with future business cycle contractions.