Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/336380 
Year of Publication: 
2023
Citation: 
[Journal:] Latin American Journal of Central Banking (LAJCB) [ISSN:] 2666-1438 [Volume:] 4 [Issue:] 4 [Article No.:] 100098 [Year:] 2023 [Pages:] 1-16
Publisher: 
Elsevier, Amsterdam
Abstract: 
The concept of centrality is widely used to monitor systems with a network structure because it allows identifying their most influential participants. This monitoring task can be difficult if the number of system participants is considerably large or if the wide variety of centrality measures currently available produce non-coincident (or mixed) signals. This document uses robust principal component analysis to evaluate a set of centrality measures calculated for the financial institutions that participate in Colombia's four financial market infrastructures. The results obtained are used to construct general indices of centrality, using the most robust measures of centrality as inputs and leaving aside those considered redundant.
Subjects: 
Centrality
Robust principal component analysis
Redundancy analysis
Clustering analysis
JEL: 
G20
C38
C23
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-nc-nd Logo
Document Type: 
Article

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