Dynamic industry uncertainty networks and the business cycle

TL;DR

This paper demonstrates that industry-specific uncertainty networks derived from option prices can predict business cycles, with certain sectors acting as key uncertainty hubs that signal upcoming economic contractions.

Contribution

It introduces a method to extract and analyze industry uncertainty networks from option prices, highlighting their predictive power for business cycles and identifying sector roles as uncertainty hubs.

Findings

Uncertainty networks contain valuable information for business cycle prediction.

Communication, industrials, and IT sectors act as uncertainty hubs.

Tighter uncertainty networks are associated with future economic contractions.

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.