Identifying central bank liquidity super-spreaders in interbank funds networks

Abstract

Evidence suggests that the Colombian interbank funds market is an inhomogeneous and hierarchical network in which a few financial institutions fulfill the role of "super-spreaders" of central bank liquidity among market participants. Results concur with evidence from other interbank markets and other financial networks regarding the flaws of traditional direct financial contagion models based on homogeneous and non-hierarchical networks, and provide further evidence about financial networks' self-organization emerging from complex adaptive financial systems. Our research work contributes to central bank's efforts by (i) examining and characterizing the actual connective structure of interbank funds networks; (ii) identifying those financial institutions that may be considered as the most important conduits for monetary policy transmission, and the main drivers of contagion risk within the interbank funds market; (iii) providing new elements for the implementation of monetary policy and for safeguarding financial stability.

The interbank network across the global financial crisis: Evidence from Italy

“…Martínez-Jaramillo et al (2014) analyze the structures of the payments and exposures networks of the Mexican interbank market, showing that only the exposures network changed after the collapse of Lehman Brothers. León et al (2016) show that the Colombian interbank market also has the small world and core-periphery structure of many other interbank markets, and propose a methodology to identify those financial institutions that may be the most important conduits not only for monetary policy transmission, but also for contagion. Finally, Craig and von Peter (2014) develop a procedure to fit a core-periphery model to realworld networks and apply it to German data.…”

Colombian liberalization and integration to world trade markets: Much ado about nothing

“…HITS algorithm) to study the importance of countries in trade networks (see Ospina, 2013, Soyyigit & Yavuzaslan, 2018 and global input-output networks (see Soyyigit & Boz, 2017). Also, they have been used to study network importance in interbank cross-border flows (see Eren & Soyyigit, 2017) and interbank networks (see León, Machado, & Sarmiento, 2018). 19 As reported in Criscuolo and Timmis (2018), this is remarkably important because becoming more central as a customer or a supplier in the global value chains is associated with faster productivity growth (of firms).…”

Las transferencias procesadas por ACH Colombia: un análisis desde la perspectiva de topología de redes

“…asimétrica), ya sea aproximándose a una distribución libre de escala (Boss et al, 2004;Inaoka et al, 2004;Soramäki et al, 2007;Bech & Atalay, 2010) u otro tipo de distribución sesgada de las conexiones (Martínez-Jaramillo et al, 2014;Craig & von Peter, 2014;Fricke & Lux, 2014, 2015. En el caso colombiano se ha documentado la presencia de redes financieras que, aproximadamente, siguen la distribución libre de escala (Cepeda, 2008;León & Berndsen, 2014;León, Machado & Sarmiento, 2016a). Por tanto, se ha caracterizado a las redes financieras típicas como robustas pero frágiles (ver Haldane, 2009y Hüser, 2015.…”

“…Esta distancia sugiere que la mayoría de las instituciones financieras requieren de otra que haga las veces de conector, presumiblemente asemejándose a una estructura centro-periferia como aquella documentada por Craig y von Peter (2014) y Fricke y Lux (2014) para el caso alemán e italiano, respectivamente. Así mismo, el coeficiente de agrupamiento de las redes financieras, por lo general, se aleja de cero (Boss et al, 2004;Becher et al, 2008;Pröpper et al, 2008;Bech & Atalay, 2010;Martínez-Jaramillo et al, 2014;León & Berndsen, 2014;León et al, 2016a), lo cual refleja que existe algún grado de transitividad en las conexiones, similar a lo documentado para redes sociales.…”

“…Respecto a la correlación por número de conexiones de los vértices, la evidencia empírica está dividida: algunos autores encuentran correlaciones negativas respecto del número de conexiones de los vértices (Soramäki et al, 2007;Bech & Atalay, 2010), y otros positivas (León & Berndsen, 2014;León et al, 2016a). Recientemente se ha reportado que las redes sociales pueden presentar correlaciones por número de conexiones con signo positivo, neutro o negativo (Csermely et al, 2013;Li et al, 2014).…”