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ResumenEn el presente trabajo se muestra evidencia para rechazar la Hipótesis de Mercado Eficiente (HME) a través de la anomalía efecto día (day effect). Se utilizan dos aproximaciones: la primera, bajo el supuesto de normalidad, estima un modelo lineal que corrobora los hallazgos de estudios anteriores sobre un efecto significativo del día de la semana sobre el retorno. La segunda, flexibiliza el supuesto de normalidad aplicando pruebas no paramétricas, y confirma los resultados de la primera aproximación. Se utilizó el IGBC y una versión diversificada deéste, la cual responde a la alta concentración delíndice en pocas acciones. Este documento corrobora los resultados de otras investigaciones basadas en métodos paramétricos, y adicionalmente, a partir de pruebas no paramétricas, muestra que existe un efecto día significativo.Palabras claves: eficiencia de mercado, hipótesis de mercado eficiente, métodos no paramétricos, IGBC, retornos.Clasificación JEL: G14, C13, C14. * Las opiniones contenidas en este documento son de responsabilidad exclusiva de los autores y no comprometen al Banco de la República ni a su Junta Directiva. Agradecimiento por los comentarios y sugerencias de

Since correlation may be interpreted as a measure of the influence across time-series, it may be conveniently mapped into a distance and into a weighted adjacency matrix. Based on such matrix, network theory has attempted to filter out the noise in correlation matrices by extracting the dominant hierarchy (i.e. the strongest linear-dependence signals) within time-series.The aim of this brief paper is to find the current hierarchy in the sovereigns' CDS market after the structural shift caused by the failure of Lehman Brothers. Thus, based on two different correlation-into-distance mapping techniques and a minimal spanning tree-based correlation-filtering methodology on 36 sovereign CDS spread time-series, the target is to identify which sovereigns are providing the strongest -less noisy-and most informative signals.The resulting sovereigns' CDS market hierarchy agrees with prior findings of Gilmore et al. (2010) regarding sovereigns' bonds market, such as the importance of geographical clustering and the idiosyncratic nature of Japan and United States. Additionally, results (i) confirm that a small set of common factors affect the entire system; (ii) identify the relevance of credit rating clustering; (iii) identify Russia, Turkey and Brazil as regional benchmarks; (iv) suggest that lowermedium grade rated sovereigns are the most influential, but also the most prone to contagion; and (v) suggest the existence of a "Latin American common factor".

We study the network of Colombian sovereign securities settlements. With data from the settlement market infrastructure we study financial institutions' transactions from three different trading and registering individual networks that we combine into a multi-layer network. Examining this network of networks enables us to confirm that (i) studying isolated single-layer trading and registering networks yields a misleading perspective on the relations between and risks induced by participating financial institutions; (ii) a multi-layer approach produces a connective structure consistent with most real-world networks (e.g. sparse, inhomogeneous, and clustered); and (iii) the multi-layer network is a multiplex that preserves the main connective features of its constituent layers due to positively correlated multiplexity. The results highlight the importance of mapping and understanding how financial institutions relate to each other across multiple financial environments, and the value of financial market infrastructures as sources of data that may help to overcome the main obstacles for working on multi-layer financial networks.