@article{91265c0703a74795bc22a2e2e71cb956,
title = "Assessing the risk of default propagation in interconnected sectoral financial networks",
abstract = "Systemic risk of financial institutions and sectoral companies relies on their inter-dependencies. The inter-connectivity of the financial networks has proven to be crucial to understand the propagation of default, as it plays a central role to assess the impact of single default events in the full system. Here, we take advantage of complex network theory to shed light on the mechanisms behind default propagation. Using real data from the BBVA, the second largest bank in Spain, we extract a financial network from customer-supplier transactions among more than 140 , 000 companies, and their economic flows. Then, we introduce a computational model, inspired by the probabilities of default contagion, that allow us to obtain the main statistics of default diffusion given the network structure at individual and system levels. Our results show the exposure of different sectors to default cascades, therefore allowing for a quantification and ranking of sectors accordingly. This information is relevant to propose countermeasures to default propagation in specific scenarios.",
keywords = "Complex systems, Default analysis, Financial networks, Financial sector analytics, SIS propagation models",
author = "Adri{\`a} Barja and Alejandro Mart{\'i}nez and Alex Arenas and Pablo Fleurquin and J. Nin and Ramasco, {Jos{\'e} J.} and Elena Tom{\'a}s",
note = "Funding Information: The dataset is not publicly available. It was acquired by BBVA. Any of the authors based at BBVA may be contacted for further details about the dataset. Funding Information: JJR acknowledge partial funding from the Spanish Ministry of Science, Innovation and Universities, the National Agency for Research Funding AEI and FEDER (EU) under the grant PACSS (RTI2018-093732-B-C22) and the Maria de Maeztu program for Units of Excellence in R&D (MDM-2017-0711). AA acknowledges support by Spanish Ministry of Science, Innovation and Universities (grant PGC2018-094754-B-C21), Generalitat de Catalunya (grant 2017SGR896), Universitat Rovira i Virgili (grant 2017PFRURV-B2-41), ICREA Academia and the James S. McDonnell Foundation (grant 220020325). We acknowledge support of the publication fee by the CSIC Open Access Publication Support Initiative through its Unit of Information Resources for Research (URICI). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Availability of data and materials Publisher Copyright: {\textcopyright} 2019, The Author(s).",
year = "2019",
month = dec,
day = "1",
doi = "10.1140/epjds/s13688-019-0211-y",
language = "English",
volume = "8",
journal = "EPJ Data Science",
issn = "2193-1127",
publisher = "Springer Science + Business Media",
number = "1",
}