Cookies?
Library Header Image
LSE Research Online LSE Library Services

Dynamic industry uncertainty networks and the business cycle

Baruník, Jozef, Bevilacqua, Mattia and Faff, Robert (2024) Dynamic industry uncertainty networks and the business cycle. Journal of Economic Dynamics and Control, 159. ISSN 0165-1889

Full text not available from this repository.

Identification Number: 10.1016/j.jedc.2023.104793

Abstract

This paper identifies smoothly varying industry uncertainty networks from option prices that contain valuable information about business cycles, especially in terms of forecasting. Such information is stronger when the network is formed on uncertainty hubs, firms identified as the main contributors to uncertainty shocks. The stronger predictive ability of the hubs-based network is robust to a wide range of checks, the inclusion of a large set of controls, and is also confirmed out-of-sample.

Item Type: Article
Official URL: https://www.sciencedirect.com/journal/journal-of-e...
Additional Information: © 2023 Elsevier B.V.
Divisions: Systemic Risk Centre
Subjects: H Social Sciences > HB Economic Theory
Date Deposited: 18 Dec 2023 09:30
Last Modified: 07 Jun 2024 18:57
URI: http://eprints.lse.ac.uk/id/eprint/121089

Actions (login required)

View Item View Item