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The drivers of systemic risk in financial networks : a data-driven machine learning analysis
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Alexandre, Michel, Silva, Thiago Christiano, Connaughton, Colm and Rodrigues, Francisco A. (2021) The drivers of systemic risk in financial networks : a data-driven machine learning analysis. Chaos, Solitons & Fractals, 153 (Part 1). 111588. doi:10.1016/j.chaos.2021.111588 ISSN 0960-0779.
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WRAP-Systemic-risk-financial-networks-data-driven-machine-learning-analysis-2021.pdf - Accepted Version - Requires a PDF viewer. Available under License Creative Commons Attribution Non-commercial No Derivatives 4.0. Download (734Kb) | Preview |
Official URL: https://doi.org/10.1016/j.chaos.2021.111588
Abstract
The purpose of this paper is to assess the role of financial variables and network topology as determinants of systemic risk (SR). The SR, for different levels of the initial shock, is computed for institutions in the Brazilian interbank market by applying the differential DebtRank methodology. The financial institution(FI)-specific determinants of SR are evaluated through two machine learning techniques: XGBoost and random forest. Shapley values analysis provided a better interpretability for our results. Furthermore, we performed this analysis separately for banks and credit unions. We have found the importance of a given feature in driving SR varies with i) the level of the initial shock, ii) the type of FI, and iii) the dimension of the risk which is being assessed – i.e., potential loss caused by (systemic impact) or imputed to (systemic vulnerability) the FI. Systemic impact is mainly driven by topological features for both types of FIs. However, while the importance of topological features to the prediction of systemic impact of banks increases with the level of the initial shock, it decreases for credit unions. Concerning systemic vulnerability, this is mainly determined by financial features, whose importance increases with the initial shock level for both types of FIs.
Item Type: | Journal Article | ||||||||
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Divisions: | Faculty of Science, Engineering and Medicine > Research Centres > Centre for Complexity Science Faculty of Science, Engineering and Medicine > Science > Mathematics |
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SWORD Depositor: | Library Publications Router | ||||||||
Journal or Publication Title: | Chaos, Solitons & Fractals | ||||||||
Publisher: | Pergamon | ||||||||
ISSN: | 0960-0779 | ||||||||
Official Date: | December 2021 | ||||||||
Dates: |
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Volume: | 153 | ||||||||
Number: | Part 1 | ||||||||
Article Number: | 111588 | ||||||||
DOI: | 10.1016/j.chaos.2021.111588 | ||||||||
Status: | Peer Reviewed | ||||||||
Publication Status: | Published | ||||||||
Access rights to Published version: | Restricted or Subscription Access | ||||||||
Date of first compliant deposit: | 5 January 2022 | ||||||||
Date of first compliant Open Access: | 5 January 2022 |
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