Los determinantes de la rentabilidad primaria de los bonos de titulización hipotecaria: la influencia de las estructuras multitramo

[ES] Este artículo analiza los determinantes de la rentabilidad primaria de los bonos de titulización hipotecaria (conocidos en la literatura como mortgage backed securities, o MBS) emitidos en España durante el periodo 1993-2011, periodo en el que el mercado español llegó a convertirse en el más importante de Europa continental. Los resultados obtenidos sobre el análisis de la población completa de MBS emitidos (262 tramos configurados sobre 94 fondos de titulización) indican que la estructuración multitramo de los MBS ha ayudado a reducir el riesgo percibido global de las emisiones de MBS, mediante la generación de mercados más completos y la reducción de los problemas derivados de la existencia de asimetrías informativas implícitas en el proceso de selección de los activos transmitidos por parte de la entidad cedente. Esta reducción del riesgo percibido ha tenido un efecto directo sobre la rentabilidad ofrecida por los bonos de titulización emitidos. Además, no se encuentran evidencias de que la emisión de MBS persiga la transmisión efectiva de riesgos, más bien al contrario. Las Entidades de crédito, por lo general, han retenido los tramos de primeras pérdidas, lo que ha contribuido a mantener en niveles muy bajos (por debajo de la rentabilidad de la deuda soberana) la rentabilidad ofrecida por los MBS. Precisamente, el escaso diferencial ofrecido por los bonos de titulización se debe a que los tramos retenidos no han ofrecido primas de rentabilidad ajustadas al riesgo inherente.

Inferring Population Genetic Structure in Widely and Continuously Distributed Carnivores: The Stone Marten (Martes foina) as a Case Study

The stone marten is a widely distributed mustelid in the Palaearctic region that exhibits variable habitat preferences in different parts of its range. The species is a Holocene immigrant from southwest Asia which, according to fossil remains, followed the expansion of the Neolithic farming cultures into Europe and possibly colonized the Iberian Peninsula during the Early Neolithic (ca. 7,000 years BP). However, the population genetic structure and historical biogeography of this generalist carnivore remains essentially unknown. In this study we have combined mitochondrial DNA (mtDNA) sequencing (621 bp) and microsatellite genotyping (23 polymorphic markers) to infer the population genetic structure of the stone marten within the Iberian Peninsula. The mtDNA data revealed low haplotype and nucleotide diversities and a lack of phylogeographic structure, most likely due to a recent colonization of the Iberian Peninsula by a few mtDNA lineages during the Early Neolithic. The microsatellite data set was analysed with a) spatial and non-spatial Bayesian individual-based clustering (IBC) approaches (STRUCTURE, TESS, BAPS and GENELAND), and b) multivariate methods [discriminant analysis of principal components (DAPC) and spatial principal component analysis (sPCA)]. Additionally, because isolation by distance (IBD) is a common spatial genetic pattern in mobile and continuously distributed species and it may represent a challenge to the performance of the above methods, the microsatellite data set was tested for its presence. Overall, the genetic structure of the stone marten in the Iberian Peninsula was characterized by a NE-SW spatial pattern of IBD, and this may explain the observed disagreement between clustering solutions obtained by the different IBC methods. However, there was significant indication for contemporary genetic structuring, albeit weak, into at least three different subpopulations. The detected subdivision could be attributed to the influence of the rivers Ebro, Tagus and Guadiana, suggesting that main watercourses in the Iberian Peninsula may act as semi-permeable barriers to gene flow in stone martens. To our knowledge, this is the first phylogeographic and population genetic study of the species at a broad regional scale. We also wanted to make the case for the importance and benefits of using and comparing multiple different clustering and multivariate methods in spatial genetic analyses of mobile and continuously distributed species.