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
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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 |
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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: | 10 Aug 2024 07:03 |
URI: | http://eprints.lse.ac.uk/id/eprint/121089 |
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