Multichannel contagion and systemic stabilisation strategies in interconnected financial markets
- Submitting institution
-
Goldsmiths' College
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 3450
- Type
- D - Journal article
- DOI
-
10.1080/14697688.2017.1357973
- Title of journal
- Quantitative Finance
- Article number
- -
- First page
- 1885
- Volume
- 17
- Issue
- 12
- ISSN
- 1469-7688
- Open access status
- Technical exception
- Month of publication
- September
- Year of publication
- 2017
- URL
-
http://research.gold.ac.uk/id/eprint/27286/
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
3
- Research group(s)
-
-
- Citation count
- 0
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Innovative data science modelling approaches such as tensorial multilayer networks are used to relate underlying economic data and how to extend the network to cover financial market information. Measuring systemic risk is an important step towards understanding financial stability. The stability of the banking system is monitored by knowing whether the given contagion process on the network is converging or diverging. We model and estimate the individual bank’s contribution to the systemic risk. The proposed stabilisation strategy guides how the central banks can impose capital surcharges on the banks in the network based on the individual bank’s systemic risk indexes.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -