从交易数据中识别银行间贷款、利率和索赔网络

Carlos León, Jorge Cely, Carlos Cadena
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引用次数: 7

摘要

我们通过实施Furfine的方法来识别来自哥伦比亚大额支付系统的银行间(即非抵押)贷款。在从交易数据中确定银行间贷款后,我们无需依赖金融机构报告的数据即可获得银行间利率和债权。将已识别的贷款与金融机构报告数据中合并的贷款进行对比,表明该算法表现良好,并且对其设置的变化具有鲁棒性。交易数据隐含的加权平均利率与本地银行间基准利率严格匹配。从已识别的贷款中,我们还建立了银行间索赔网络。三个主要产出(即银行间贷款、利率和债权网络)对于检查和监测货币市场、对比金融机构报告的数据以及作为金融传染和系统性风险模型的输入是有价值的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Identifying Interbank Loans, Rates, and Claims Networks from Transactional Data
We identify interbank (i.e. non-collateralized) loans from the Colombian large-value payment system by implementing Furfine’s method. After identifying interbank loans from transactional data we obtain the interbank rates and claims without relying on financial institutions’ reported data. Contrasting identified loans with those consolidated from financial institutions’ reported data suggests the algorithm performs well, and it is robust to changes in its setup. The weighted average rate implicit in transactional data matches local interbank rate benchmarks strictly. From identified loans we also build the interbank claims network. The three main outputs (i.e. the interbank loans, the rates, and the claims networks) are valuable for examining and monitoring the money market, for contrasting data reported by financial institutions, and as inputs in models of financial contagion and systemic risk.
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