Dynamic industry uncertainty networks and the business cycle
Baruník, J., Bevilacqua, M. & Faff, R.
(2024).
Dynamic industry uncertainty networks and the business cycle.
Journal of Economic Dynamics and Control,
159,
https://doi.org/10.1016/j.jedc.2023.104793
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 |
|---|---|
| Copyright holders | © 2023 Elsevier B.V. |
| Departments | LSE > Research Centres > Financial Markets Group > Systemic Risk Centre |
| DOI | 10.1016/j.jedc.2023.104793 |
| Date Deposited | 18 Dec 2023 |
| Acceptance Date | 20 Nov 2023 |
| URI | https://researchonline.lse.ac.uk/id/eprint/121089 |
Explore Further
- https://www.systemicrisk.ac.uk/people/mattia-bevilacqua (Author)
- https://www.scopus.com/pages/publications/85178233044 (Scopus publication)
- https://www.sciencedirect.com/journal/journal-of-e... (Official URL)