The DOI matches its Crossref record; 30 of the 30 references it cites were found in a registry or an index.
Measuring the Frequency Dynamics of Financial Connectedness and Systemic Risk*
Open accessAbstract
We propose a new framework for measuring connectedness among financial variables that arise due to heterogeneous frequency responses to shocks. To estimate connectedness in short-, medium-, and long-term financial cycles, we introduce a framework based on the spectral representation of variance decompositions. In an empirical application, we document the rich time-frequency dynamics of volatility connectedness in U.S. financial institutions. Economically, periods in which connectedness is created at high frequencies are periods when stock markets seem to process information rapidly and calmly, and a shock to one asset in the system will have an impact mainly in the short term. When the connectedness is created at lower frequencies, it suggests that shocks are persistent and are being transmitted for longer periods.
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Cites
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On the network topology of variance decompositions: Measuring the connectedness of financial firms
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Cited by
Network connectedness of green bonds and asset classes
Reboredo, J. C., Ugolini, A., & Aiube, F. A. L. (2020) · Energy Economics · doi:10.1016/j.eneco.2019.104629 · Cited by 348
Yousaf, I., & Yarovaya, L. (2022) · Finance Research Letters · doi:10.1016/j.frl.2022.103175 · Cited by 79
The state-of-play in maritime economics and logistics research (2017–2023)
Haralambides, H. (2023) · Maritime Economics & Logistics · doi:10.1057/s41278-023-00265-x · Cited by 16
Metadata
- Authors
- Baruník, J., & Křehlík, T.
- Venue
- Journal of Financial Econometrics
- Publisher
- Oxford University Press (OUP)
- Published
- 2018
- Volume
- 16
- Issue
- 2
- Pages
- 271-296
- ISSN
- 1479-8409 (ISSN-L)
- 1479-8417
- OpenAlex
- W2949333925
- Cited by
- 1,766
- References
- 30
- FWCI
- 83.18
- Type
- journal article
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
