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Dynamic industry uncertainty networks and the business cycle

Jozef Baruník (), Mattia Bevilacqua and Robert Faff

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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.

Date: 2021-01, Revised 2021-03
New Economics Papers: this item is included in nep-ict and nep-net
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