Identificación del Riesgo Sistémico en la Banca Múltiple: un enfoque de Redes Bipartitas
Issue | Vol. 7 Núm. 2 (2023): Ciencia, Economía y Negocios |
DOI | |
Publicado | dic 29, 2023 |
Estadísticas |
Instituto Tecnológico de Santo Domingo (INTEC), República Dominicana
Instituto Tecnológico de Santo Domingo (INTEC), República Dominicana
Resumen
El sistema financiero puede representarse como una gran red compleja en la que los bancos están interconectados entre sí a través de vínculos financieros visibles e invisibles. En este trabajo se presenta un modelo que permite analizar un sistema financiero mediante un enfoque de teoría de redes, el cual constituye una herramienta práctica de monitoreo y diagnóstico para entes reguladores al permitir identificar las vulnerabilidades que surgen a medida que los bancos se vuelven cada vez más interconectadas, un choque en una red financiera puede provocar importantes fallas en cascada en todo un sistema, en otras palabras, riesgo sistémico. Para estudiar el riesgo sistémico del sector financiero dominicano, se crea un modelo de red financiera bipartita compuesto por dos tipos de nodos, (i) bancos múltiples (o comerciales) y (ii) cartera de crédito -segmentada por sector económico-, el cual prueba la influencia de cada crédito en particular o grupo de créditos en los bancos múltiples en general, y se implementa una prueba de estrés para evaluar la vulnerabilidad de la red ante el impacto en la cartera de crédito como consecuencia de sucesos externos en los distintos sectores económicos del país.
Aldasoro, I., Gatti, D., Faia, E., (2016). “Bank networks: contagion, systemic risk and prudential policy”. BIS Working Papers No. 597. Bank for International Settlements. https://www.bis.org/publ/work597.pdf
Aoyama, H., Battiston, S., Fujiwara, Y., (2013). “DebtRank Analysis of the Japanese Credit Network”. Kyoto University and Research Institute of Economy, Trade and Industry. https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=51c7f4412b5a64c1b89c33e2835082943421afe9
Battiston, S., Caldarelli, G., Pirotte, H., Bersini, H., Roukny, T., (2013). “Default Cascades in Complex Networks: Topology and Systemic Risk”. Scientific Reports. http://dx.doi.org/10.1038/srep02759
Battiston, S., Tasca, P., Kaushik, R., Caldarelli, G., (2012). “DebtRank: Too Central to Fail? Financial Networks, the FED and Systemic Risk”. Scientific Reports. https://doi.org/10.1038/srep00541
Billio, M., Casarin, R., Costola, M., Iacopini, M., (2021). “COVID-19 spreading in financial networks: A semiparametric matrix regression model”. Econometrics and Statistics. https://doi.org/10.1016/j.ecosta.2021.10.003
Bonaccolto, G., Caporin, M., Panzica, R., (2017). “Estimation and Model-Based Combination of Causality Networks”. SAFE Working Paper No. 165. http://dx.doi.org/10.2139/ssrn.2909585
Caccioli, F., Shrestha, M., Moore, C., Farmer, J. D., (2014). “Stability analysis of financial contagion due to overlapping portfolios”. Journal of Banking & Finance. Pages 233-245. https://doi.org/10.1016/j.jbankfin.2014.05.021
Cáceres, J., (2017). “Riesgo de contagio en el sistema financiero boliviano – Análisis a través de redes de pagos interbancarios y del financiamiento de operaciones de crédito a empresas”. Revista de Análisis, Volumen N° 27, pp. 91-118. Banco Central de Bolivia. https://www.bcb.gob.bo/webdocs/publicacionesbcb/revista_analisis/ra_vol27/articulo_4_v27.pdf
Cadavid, L., (2019). “Medición del Riesgo Sistémico Intra-bancario”. Universidad EAFIT. https://repository.eafit.edu.co/handle/10784/16060
Chan-Lau, J., (2010). “Balance Sheet Network Analysis of Too-Connected-ToFail Risk in Global and Domestic Banking Systems”. SSRN Electronic Journal. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1566442
Chavarría, E., (2014). “Redes Bancarias y Riesgo Sistémico: Desarrollo de un Algoritmo de Análisis y Diagnóstico”. Universidad de Chile. https://repositorio.uchile.cl/handle/2250/130258
Cihak, M., (2007). “Introduction to Applied Stress Testing”. IMF Working Paper WP/07/59. https://www.imf.org/external/pubs/ft/wp/2007/wp0759.pdf
Das, S., (2016). “Matrix Metrics: Network-Based Systemic Risk Scoring”. The Journal of Alternative Investments. https://srdas.github.io/Papers/JAI_Das_issue.pdf
De Castro, R., Miranda, B., (2013). “Contagion Risk within Firm-Bank Bivariate Networks”. Banco Central de Brasil. Working Papers No. 322, p. 1-60. https://www.bcb.gov.br/pec/wps/ingl/wps322.pdf
Diestel, R., (2010). “Graph Theory: 4th ed”. University of Hamburg.. https://link.springer.com/10.1007/978-3-642-14279-6
Garcia, J., (2017). “Representación gráfica de redes bipartitas basada en descomposicion k-core”. Universidad Politécnica de Madrid. https://oa.upm.es/49329/
Gómez, J., Hirs, J., Sanin, S., (2018). “Dynamic relations between oil and stock markets: Volatility spillovers, networks and causality”. Borradores de Economía No. 1051. Banco de la República de Colombia. https://repositorio.banrep.gov.co/bitstream/handle/20.500.12134/9389/be_1051.pdf
Huang, X., Vodenska, I., Havlin, S., Stanley, H., (2013). “Cascading Failures in Bi-partite Graphs: Model for Systemic Risk Propagation”. Sci Rep 3, 1219. Nature Scientific Reports. https://doi.org/10.1038/srep01219
Landaberry, V., Caccioli, F., Rodriguez, A., Baron, A., Martinez, S., Lluberas, R., (2021). “The contribution of the intra-firm exposures network to systemic risk”. Latin American Journal of Central Banking. https://doi.org/10.1016/j.latcb.2021.100032
Lavin, J., Valle, M., Magner, N., (2019). “Modeling Overlapped Mutual Funds’ Portfolios: A Bipartite Network Approach”. Volume 2019, Article ID 1565698, 20 Pages. Complexity. https://doi.org/10.1155/2019/1565698
León, C., Berndsen, R., (2014). “Rethinking financial stability: Challenges arising from financial networks’ modular scale-free architecture”. Journal of Financial Stability. http://dx.doi.org/10.1016/j.jfs.2014.10.006
Maino, R., Tintchev, K., (2012). “From Stress to Costress: Stress Testing Interconnected Banking Systems”. IMF Working Papers. https://www.imf.org/en/Publications/WP/Issues/2016/12/31/From-Stress-to-Costress-Stress-Testing-Interconnected-Banking-Systems-25734
Martinez-Jaramillo, S., Alexandrova-Kabadjova, B., Bravo-Benitez, B., Solorzano-Margain, J., (2012). “An Empirical Study of the Mexican Banking System’s Network and Its Implications for Systemic Risk”. Bank of México. Working Paper 2012-07. http://dx.doi.org/10.2139/ssrn.2140144
Martinez-Jaramillo, S., Alexandrova-Kabadjova, B., Bravo-Benitez, B., Solorzano-Margain, J., (2014). “An Empirical Study of the Mexican Banking System’s Network and Its Implications for Systemic Risk”. Article. Journal of Economic Dynamics and Control Volume 40, Pages 242-265. https://doi.org/10.1016/j.jedc.2014.01.009
Mitchell, J.C., (1969). “The Concept and Use of Social Networks”. In J. C. Mitchell (Ed), SocialNetworks in Urban Situations. Manchester, UK: Manchester University Press. https://seminariosocioantropologia.files.wordpress.com/2014/03/c-mitcell-concept-and-use-social-network.pdf
Naciones Unidas, Departamento de Estadísticas Económicas (2005). “Clasificación Industrial Internacional Uniforme de todas las Actividades Económicas (CIIU)”. Rev. 3.1. https://unstats.un.org/unsd/classifications/Econ/Download/In%20Text/ISIC31_Spanish.pdf
Newman, M. E. J., (2002). “Assortative Mixing in Networks”. American Physical Society Vol. 89, No. 4, pp. 208-701. https://doi.org/10.1103/PhysRevLett.89.208701
Newman, M. E. J., (2010). “Networks: An Introduction”. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199206650.001.0001
Papadimitriou, T., Gogas, P., Tabak, B., (2013). “Complex networks and banking systems supervision”. Physica A: Statistical Mechanics and its Applications. Volume 392, Issue 19, 1 October 2013, Pages 4429-4434. Science Direct https://doi.org/10.1016/j.physa.2013.05.013
Poledna, S., Martínez-Jaramillo, S., Caccioli, F., Thurner, S., (2021). “Quantification of systemic risk from overlapping portfolios in the financial system”. Volume 52. Journal of Financial Stability. https://doi.org/10.1016/j.jfs.2020.100808
Sakamoto, Y., Vodenska, I., (2016). “Systemic risk and structural changes in a bipartite bank network: a new perspective on the Japanese banking crisis of the 1990s”. Journal of Complex Networks, Volume 5, Issue 2, June 2017, Pages 315–333. https://doi.org/10.1093/comnet/cnw018
Sakamoto, Y., Vodenska, I., (2017). Erratum to “Systemic risk and structural changes in a bipartite bank network: a new perspective on the Japanese banking crisis of the 1990s”. Journal of Complex Networks, Volume 5, Issue 3, July 2017, Page 512. The Journal of Alternative Investments. https://doi.org/10.1093/comnet/cnx012
Santana, M., (2015). “El sistema financiero de la República Dominicana: Evaluación de su eficiencia y productividad mediante el Análisis Envolvente de Datos (DEA)”. Universidad de Valencia. https://roderic.uv.es/handle/10550/50617
Squartini, T., Almog, A., Caldarelli, G., Lelyveld, I., Garlaschelli, D., Cimini, G., (2017). “Enhanced capital-asset pricing model for bipartite financial networks reconstruction”. Phys. Rev. E 96, 032315. American Physical Society. https://link.aps.org/doi/10.1103/PhysRevE.96.032315
Stiglitz, J., (2000). “La economía del sector público, 3ra edición”. Columbia University Press. https://desarrollomedellin.files.wordpress.com/2018/08/stiglitz-2000-tercera-edicion.pdf
Vodenska, I., Dehmamy, N., Becker, A., Buldyrev, S., Havlin, S., (2021). “Systemic stress test model for shared portfolio networks”. Nature Scientific Reports. https://doi.org/10.1038%2Fs41598-021-82904-y
Wasserman, S., Faust, K., (1994). “Social Network Analysis: Methods and Applications”. New York: Cambridge University Press. https://doi.org/10.1525/ae.1997.24.1.219
Yanquen, E., Livan, G., Montañez, R., Martínez, S., (2022). “Measuring systemic risk for bank credit networks: A multilayer approach”. Latin American Journal of Central Banking. http://dx.doi.org/10.1016/j.latcb.2022.100049
Aoyama, H., Battiston, S., Fujiwara, Y., (2013). “DebtRank Analysis of the Japanese Credit Network”. Kyoto University and Research Institute of Economy, Trade and Industry. https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=51c7f4412b5a64c1b89c33e2835082943421afe9
Battiston, S., Caldarelli, G., Pirotte, H., Bersini, H., Roukny, T., (2013). “Default Cascades in Complex Networks: Topology and Systemic Risk”. Scientific Reports. http://dx.doi.org/10.1038/srep02759
Battiston, S., Tasca, P., Kaushik, R., Caldarelli, G., (2012). “DebtRank: Too Central to Fail? Financial Networks, the FED and Systemic Risk”. Scientific Reports. https://doi.org/10.1038/srep00541
Billio, M., Casarin, R., Costola, M., Iacopini, M., (2021). “COVID-19 spreading in financial networks: A semiparametric matrix regression model”. Econometrics and Statistics. https://doi.org/10.1016/j.ecosta.2021.10.003
Bonaccolto, G., Caporin, M., Panzica, R., (2017). “Estimation and Model-Based Combination of Causality Networks”. SAFE Working Paper No. 165. http://dx.doi.org/10.2139/ssrn.2909585
Caccioli, F., Shrestha, M., Moore, C., Farmer, J. D., (2014). “Stability analysis of financial contagion due to overlapping portfolios”. Journal of Banking & Finance. Pages 233-245. https://doi.org/10.1016/j.jbankfin.2014.05.021
Cáceres, J., (2017). “Riesgo de contagio en el sistema financiero boliviano – Análisis a través de redes de pagos interbancarios y del financiamiento de operaciones de crédito a empresas”. Revista de Análisis, Volumen N° 27, pp. 91-118. Banco Central de Bolivia. https://www.bcb.gob.bo/webdocs/publicacionesbcb/revista_analisis/ra_vol27/articulo_4_v27.pdf
Cadavid, L., (2019). “Medición del Riesgo Sistémico Intra-bancario”. Universidad EAFIT. https://repository.eafit.edu.co/handle/10784/16060
Chan-Lau, J., (2010). “Balance Sheet Network Analysis of Too-Connected-ToFail Risk in Global and Domestic Banking Systems”. SSRN Electronic Journal. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1566442
Chavarría, E., (2014). “Redes Bancarias y Riesgo Sistémico: Desarrollo de un Algoritmo de Análisis y Diagnóstico”. Universidad de Chile. https://repositorio.uchile.cl/handle/2250/130258
Cihak, M., (2007). “Introduction to Applied Stress Testing”. IMF Working Paper WP/07/59. https://www.imf.org/external/pubs/ft/wp/2007/wp0759.pdf
Das, S., (2016). “Matrix Metrics: Network-Based Systemic Risk Scoring”. The Journal of Alternative Investments. https://srdas.github.io/Papers/JAI_Das_issue.pdf
De Castro, R., Miranda, B., (2013). “Contagion Risk within Firm-Bank Bivariate Networks”. Banco Central de Brasil. Working Papers No. 322, p. 1-60. https://www.bcb.gov.br/pec/wps/ingl/wps322.pdf
Diestel, R., (2010). “Graph Theory: 4th ed”. University of Hamburg.. https://link.springer.com/10.1007/978-3-642-14279-6
Garcia, J., (2017). “Representación gráfica de redes bipartitas basada en descomposicion k-core”. Universidad Politécnica de Madrid. https://oa.upm.es/49329/
Gómez, J., Hirs, J., Sanin, S., (2018). “Dynamic relations between oil and stock markets: Volatility spillovers, networks and causality”. Borradores de Economía No. 1051. Banco de la República de Colombia. https://repositorio.banrep.gov.co/bitstream/handle/20.500.12134/9389/be_1051.pdf
Huang, X., Vodenska, I., Havlin, S., Stanley, H., (2013). “Cascading Failures in Bi-partite Graphs: Model for Systemic Risk Propagation”. Sci Rep 3, 1219. Nature Scientific Reports. https://doi.org/10.1038/srep01219
Landaberry, V., Caccioli, F., Rodriguez, A., Baron, A., Martinez, S., Lluberas, R., (2021). “The contribution of the intra-firm exposures network to systemic risk”. Latin American Journal of Central Banking. https://doi.org/10.1016/j.latcb.2021.100032
Lavin, J., Valle, M., Magner, N., (2019). “Modeling Overlapped Mutual Funds’ Portfolios: A Bipartite Network Approach”. Volume 2019, Article ID 1565698, 20 Pages. Complexity. https://doi.org/10.1155/2019/1565698
León, C., Berndsen, R., (2014). “Rethinking financial stability: Challenges arising from financial networks’ modular scale-free architecture”. Journal of Financial Stability. http://dx.doi.org/10.1016/j.jfs.2014.10.006
Maino, R., Tintchev, K., (2012). “From Stress to Costress: Stress Testing Interconnected Banking Systems”. IMF Working Papers. https://www.imf.org/en/Publications/WP/Issues/2016/12/31/From-Stress-to-Costress-Stress-Testing-Interconnected-Banking-Systems-25734
Martinez-Jaramillo, S., Alexandrova-Kabadjova, B., Bravo-Benitez, B., Solorzano-Margain, J., (2012). “An Empirical Study of the Mexican Banking System’s Network and Its Implications for Systemic Risk”. Bank of México. Working Paper 2012-07. http://dx.doi.org/10.2139/ssrn.2140144
Martinez-Jaramillo, S., Alexandrova-Kabadjova, B., Bravo-Benitez, B., Solorzano-Margain, J., (2014). “An Empirical Study of the Mexican Banking System’s Network and Its Implications for Systemic Risk”. Article. Journal of Economic Dynamics and Control Volume 40, Pages 242-265. https://doi.org/10.1016/j.jedc.2014.01.009
Mitchell, J.C., (1969). “The Concept and Use of Social Networks”. In J. C. Mitchell (Ed), SocialNetworks in Urban Situations. Manchester, UK: Manchester University Press. https://seminariosocioantropologia.files.wordpress.com/2014/03/c-mitcell-concept-and-use-social-network.pdf
Naciones Unidas, Departamento de Estadísticas Económicas (2005). “Clasificación Industrial Internacional Uniforme de todas las Actividades Económicas (CIIU)”. Rev. 3.1. https://unstats.un.org/unsd/classifications/Econ/Download/In%20Text/ISIC31_Spanish.pdf
Newman, M. E. J., (2002). “Assortative Mixing in Networks”. American Physical Society Vol. 89, No. 4, pp. 208-701. https://doi.org/10.1103/PhysRevLett.89.208701
Newman, M. E. J., (2010). “Networks: An Introduction”. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199206650.001.0001
Papadimitriou, T., Gogas, P., Tabak, B., (2013). “Complex networks and banking systems supervision”. Physica A: Statistical Mechanics and its Applications. Volume 392, Issue 19, 1 October 2013, Pages 4429-4434. Science Direct https://doi.org/10.1016/j.physa.2013.05.013
Poledna, S., Martínez-Jaramillo, S., Caccioli, F., Thurner, S., (2021). “Quantification of systemic risk from overlapping portfolios in the financial system”. Volume 52. Journal of Financial Stability. https://doi.org/10.1016/j.jfs.2020.100808
Sakamoto, Y., Vodenska, I., (2016). “Systemic risk and structural changes in a bipartite bank network: a new perspective on the Japanese banking crisis of the 1990s”. Journal of Complex Networks, Volume 5, Issue 2, June 2017, Pages 315–333. https://doi.org/10.1093/comnet/cnw018
Sakamoto, Y., Vodenska, I., (2017). Erratum to “Systemic risk and structural changes in a bipartite bank network: a new perspective on the Japanese banking crisis of the 1990s”. Journal of Complex Networks, Volume 5, Issue 3, July 2017, Page 512. The Journal of Alternative Investments. https://doi.org/10.1093/comnet/cnx012
Santana, M., (2015). “El sistema financiero de la República Dominicana: Evaluación de su eficiencia y productividad mediante el Análisis Envolvente de Datos (DEA)”. Universidad de Valencia. https://roderic.uv.es/handle/10550/50617
Squartini, T., Almog, A., Caldarelli, G., Lelyveld, I., Garlaschelli, D., Cimini, G., (2017). “Enhanced capital-asset pricing model for bipartite financial networks reconstruction”. Phys. Rev. E 96, 032315. American Physical Society. https://link.aps.org/doi/10.1103/PhysRevE.96.032315
Stiglitz, J., (2000). “La economía del sector público, 3ra edición”. Columbia University Press. https://desarrollomedellin.files.wordpress.com/2018/08/stiglitz-2000-tercera-edicion.pdf
Vodenska, I., Dehmamy, N., Becker, A., Buldyrev, S., Havlin, S., (2021). “Systemic stress test model for shared portfolio networks”. Nature Scientific Reports. https://doi.org/10.1038%2Fs41598-021-82904-y
Wasserman, S., Faust, K., (1994). “Social Network Analysis: Methods and Applications”. New York: Cambridge University Press. https://doi.org/10.1525/ae.1997.24.1.219
Yanquen, E., Livan, G., Montañez, R., Martínez, S., (2022). “Measuring systemic risk for bank credit networks: A multilayer approach”. Latin American Journal of Central Banking. http://dx.doi.org/10.1016/j.latcb.2022.100049
Riesgo sistémico
redes financieras bipartitas
contagio
regulación macroprudencial
prueba de estrés
- Resumen visto - 387 veces
- PDF descargado - 193 veces
- HTML descargado - 52 veces
- XML descargado - 106 veces
- ePUB descargado - 13 veces
Descargas
Los datos de descargas todavía no están disponibles.
Licencia
Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-CompartirIgual 4.0.
Copyright
© Ciencia, Economía y Negocios, 2024
Afiliaciones
Petra M. Goico Castillo
Instituto Tecnológico de Santo Domingo (INTEC), República Dominicana
Felipe Llaugel
Instituto Tecnológico de Santo Domingo (INTEC), República Dominicana
Cómo citar
Goico Castillo, P. M., & Llaugel, F. (2023). Identificación del Riesgo Sistémico en la Banca Múltiple: un enfoque de Redes Bipartitas. Ciencia, Economía Y Negocios, 7(2), 5–32. https://doi.org/10.22206/ceyn.2023.v7i2.2948