Constanza Martínez-Ventura, Jorge Ricardo Mariño-Martínez, Javier Miguélez-Márquez
{"title":"金融市场基础设施中中心性度量的冗余性","authors":"Constanza Martínez-Ventura, Jorge Ricardo Mariño-Martínez, Javier Miguélez-Márquez","doi":"10.32468/be.1206","DOIUrl":null,"url":null,"abstract":"The concept of centrality has been widely used to monitor systems with a network structure because it allows identifying their most influential participants. But 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 principal component analysis to evaluate a set of centrality measures calculated for the financial institutions that participate in four financial market infrastructures of Colombia. The results obtained are used to construct general indices of centrality, using the strongest measures of centrality as inputs, and leaving aside those considered redundant.","PeriodicalId":100867,"journal":{"name":"Latin American Journal of Central Banking","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Redundancy of Centrality Measures in Financial Market Infrastructures\",\"authors\":\"Constanza Martínez-Ventura, Jorge Ricardo Mariño-Martínez, Javier Miguélez-Márquez\",\"doi\":\"10.32468/be.1206\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The concept of centrality has been widely used to monitor systems with a network structure because it allows identifying their most influential participants. But 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 principal component analysis to evaluate a set of centrality measures calculated for the financial institutions that participate in four financial market infrastructures of Colombia. The results obtained are used to construct general indices of centrality, using the strongest measures of centrality as inputs, and leaving aside those considered redundant.\",\"PeriodicalId\":100867,\"journal\":{\"name\":\"Latin American Journal of Central Banking\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-08-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Latin American Journal of Central Banking\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.32468/be.1206\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Latin American Journal of Central Banking","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.32468/be.1206","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Redundancy of Centrality Measures in Financial Market Infrastructures
The concept of centrality has been widely used to monitor systems with a network structure because it allows identifying their most influential participants. But 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 principal component analysis to evaluate a set of centrality measures calculated for the financial institutions that participate in four financial market infrastructures of Colombia. The results obtained are used to construct general indices of centrality, using the strongest measures of centrality as inputs, and leaving aside those considered redundant.