Systemic Risk in European Banking: Evidence from Bivariate GARCH Models

This paper attempts to assess the Europe-wide systemic risk in banking. We employ a bivariate GARCH model to estimate conditional correlations between European bank stock indices. These correlations are used as an indication for the interdependencies amongst the banking business in Europe and hence for the systemic risk potential. We employ several tests to assess the development of systemic risk: a non-parametric test of constancy of the correlation, a test of parallel shifts in the correlation at pre-specified events, and a test for a linear time trend in the correlations. The results show that many of the conditional correlations exhibit an upward move in the last years. This is an indication that the economic factors determining the European banking business have become more similar and that the systemic risk potential has increased. --systemic risk,banking,contagion,Europe,bivariate GARCH

EXPERIENTIAL VALUE: A HIERARCHICAL MODEL, THE IMPACT ON E-LOYALTY AND A CUSTOMER TYPOLOGY

The main objective of this study is to empirically test a fourth-order hierarchical model of experiential value in an online book and CD setting. In addition, we provide empirical evidence for the role of hedonic and utilitarian value components in creating attitudinal and behavioral loyalty. Finally, we develop an online customer typology, based on the underlying value sources. Based on a sample of 190 visitors of online book and CD retailers, we used PLS to test a third and fourth order hierarchical model of experiential value, emphasizing a hedonic (intrinsic) and utilitarian (extrinsic) value component and the existence of the holistic concept of experiential value. Our results demonstrate that experiential value consists of the third order components hedonic (intrinsic) and utilitarian (extrinsic) value. Both value aspects impact attitudinal loyalty ultimately leading to behavioral loyalty which is also directly affected by utilitarian value. Finally, a nonhierarchical (k-means) cluster analysis identified four segments of online visitors: hedonists, utilitarians, active negativists, and reactive positivists.marketing ;

Female mating preferences in blind cave tetras Astyanax fasciatus (Characidae, Teleostei).

The Mexican tetra Astyanax fasciatus has evolved a variety of more or less color- and eyeless cave populations. Here we examined the evolution of the female preference for large male body size within different populations of this species, either surface- or cave-dwelling. Given the choice between visual cues from a large and a small male, females from the surface form as well as females from an eyed cave form showed a strong preference for large males. When only non-visual cues were presented in darkness, the surface females did not prefer either males. Among the six cave populations studied, females of the eyed cave form and females of one of the five eyeless cave populations showed a preference for large males. Apparently, not all cave populations of Astyanax have evolved non-visual mating preferences. We discuss the role of selection by benefits of non-visual mate choice for the evolution of non-visual mating preferences

Systemic Risk in European Banking - Evidence from Bivariate GARCH Models

This paper attempts to assess the Europe-wide systemic risk in banking. We employ a bivariate GARCH model to estimate conditional correlations between European bank stock indices. These correlations are used as an indication for the interdependencies amongst the banking business in Europe and hence for the systemic risk potential. We employ several tests to assess the development of systemic risk: a non-parametric test of constancy of the correlation, a test of parallel shifts in the correlation at pre-specified events, and a test for a linear time trend in the correlations. The results show that many of the conditional correlations exhibit an upward move in the last years. This is an indication that the economic factors determining the European banking business have become more similar and that the systemic risk potential has increased

Достоинства и недостатки мобильного банкинга для клиентов - физ. лиц

The paper studies mobile banking. In the article the advantages, disadvantages of mobile banking and tips to protect their data when using it

How Different Analysis and Interpolation Methods Affect the Accuracy of Ice Surface Elevation Changes Inferred from Satellite Altimetry

Satellite altimetry has been widely used to determine surface elevation changes in polar ice sheets. The original height measurements are irregularly distributed in space and time. Gridded surface elevation changes are commonly derived by repeat altimetry analysis (RAA) and subsequent spatial interpolation of height change estimates. This article assesses how methodological choices related to those two steps affect the accuracy of surface elevation changes, and how well this accuracy is represented by formal uncertainties. In a simulation environment resembling CryoSat-2 measurements acquired over a region in northeast Greenland between December 2010 and January 2014, different local topography modeling approaches and different cell sizes for RAA, and four interpolation approaches are tested. Among the simulated cases, the choice of either favorable or unfavorable RAA affects the accuracy of results by about a factor of 6, and the different accuracy levels are propagated into the results of interpolation. For RAA, correcting local topography by an external digital elevation model (DEM) is best, if a very precise DEM is available, which is not always the case. Yet the best DEM-independent local topography correction (nine-parameter model within a 3,000 m diameter cell) is comparable to the use of a perfect DEM, which exactly represents the ice sheet topography, on the same cell size. Interpolation by heterogeneous measurement-error-filtered kriging is significantly more accurate (on the order of 50% error reduction) than interpolation methods, which do not account for heterogeneous errors

MorphoCluster: Efficient Annotation of Plankton Images by Clustering

In this work, we present MorphoCluster, a software tool for data-driven, fast, and accurate annotation of large image data sets. While already having surpassed the annotation rate of human experts, volume and complexity of marine data will continue to increase in the coming years. Still, this data requires interpretation. MorphoCluster augments the human ability to discover patterns and perform object classification in large amounts of data by embedding unsupervised clustering in an interactive process. By aggregating similar images into clusters, our novel approach to image annotation increases consistency, multiplies the throughput of an annotator, and allows experts to adapt the granularity of their sorting scheme to the structure in the data. By sorting a set of 1.2 M objects into 280 data-driven classes in 71 h (16 k objects per hour), with 90% of these classes having a precision of 0.889 or higher. This shows that MorphoCluster is at the same time fast, accurate, and consistent; provides a fine-grained and data-driven classification; and enables novelty detection