Contagion and regulation in endogenous bank networks

We develop a simple model of endogenous bank networks to study financial contagion and how leverage regulation may affect it. Banks maximize expected profit by choosing the optimal allocation of resources between three different classes of assets. An interbank network arise as result of loans between banks, creating a direct channel of contagion in the financial system. Contagion may occur when the realized return of the risky asset is sufficiently low to make a bank insolvent, subsequently triggering a cascade effect that propagates through default in interbank loans. Contrary to what would be expected, our results show that despite forcing banks to deleverage, increasing minimum capital requirements may lead to a system with higher aggregate levels of default.

Le secret bancaire et l'entraide internationale

Parmi les indicateurs de la mondialisation, le secret bancaire est au centre d'un débat animé en ce moment historique, caractérisé par la globalisation de l'économie, les exigences de sécurité croissantes, l'urgence de la lutte contre le blanchiment des capitaux provenant d’activités criminelles et l’internationalisation expansive des réseaux bancaires. La tendance vers le renforcement de la coopération internationale, met en discussion la forte sauvegarde du secret bancaire de plusieurs pays. La question dirimante est plutôt claire. Il s'agit, effectivement, de savoir jusqu'à quel point le secret, dans sa conception la plus inextensible et inflexible, devient par contre un instrument décisif pour contourner les règles communes,faire une concurrence déloyale sur les marchés et assurer des véritables crimes, par exemple de type terroriste. Pour faire évoluer les situations jugées problématiques, la démarche parallèle des trois organismes BÂLE, l’OCDE puis le GAFI est d’autant plus significative, qu’elle a été inspirée par les préoccupations exprimées au sein du G7 sur les dangers que présenteraient pour l’économie internationale certaines activités financières accomplies sur et à partir de ces territoires. L’ordre public justifie aussi la mise en place de mesures particulières en vue d’enrayer le blanchiment des capitaux provenant du trafic des stupéfiants. Selon les pays, des systèmes plus ou moins ingénieux tentent de concilier la nécessaire information des autorités publiques et le droit au secret bancaire, élément avancé de la protection de la vie privée dont le corollaire est, entre autres, l’article 7 et 8 de la Charte canadienne des droits et libertés et l’article 8 de la Convention européenne de sauvegarde des droits de l’homme et des libertés fondamentales du citoyen, et donc de l’atteinte à ces libertés. Nous le verrons, les prérogatives exorbitantes dont bénéficient l’État, l’administration ou certains tiers, par l’exercice d’un droit de communication et d’échange d’information, constituent une véritable atteinte au principe sacré de la vie privée et du droit à la confidentialité. Cette pénétration de l’État ou de l’administration au coeur des relations privilégiées entre la banque et son client trouve certainement une justification irréfutable lorsque la protection est celle de l’intérêt public, de la recherche d’une solution juridique et judiciaire. Mais cela crée inévitablement des pressions internes et des polémiques constantes,indépendamment de l’abus de droit que l’on peut malheureusement constater dans l’usage et l’exercice de certaines prérogatives.

A model of competition and interbank network formation

This work aims to understand the interaction between competition and network formation in the banking market. Combining Matutes and Padilla (1994) and Matutes and Vives (2000), we build a model of imperfect bank competition for deposits in which an interbank relationship network is a key strategic decision: it affects banks’ profit and risk position. The competition level exerts influence in the banking network structure since it affects the network outcomes. As result, we have that different competition levels imply different network topologies. Specifically, greater competition imply denser networks. Finally, when we allow for the possibility of collusion, the denser network can come out in the least competitive environment.

Creating and modelling personal socio-economic networks in on-line banking

The banking industry is observing how new competitors threaten its millennial business model by targeting unbanked people, offering new financial services to their customer base, and even enabling new channels for existing services and customers. The knowledge on users, their behaviour, and expectations become a key asset in this new context. Well aware of this situation, the Center for Open Middleware, a joint technology center created by Santander Bank and Universidad Politécnica de Madrid, has launched a set of initiatives to allow the experimental analysis and management of socio-economic information. PosdataP2P service is one of them, which seeks to model the economic ties between the holders of university smart cards, leveraging on the social networks the holders are subscribed to. In this paper we describe the design principles guiding the development of the system, its architecture and some implementation details.

Improving retail banking staff incentive systems

This Work Project seeks to analyze the viability, utility and best way of implementing mechanisms of double accounting and of insertion of low (or null) sales objectives in an incentives program. The main findings are that both processes are possible and to a certain extent advisable, although in very specific ways and with some limitations. Double accounting processes are especially effective between different segments and networks and should have a greater impact in the first evaluation periods of each case and the null objectives, albeit usable, are recommended to be always substituted by positive objectives, even if quite small. Moreover, it is concluded that the formal structure of the incentives program influences significantly these concepts, namely concerning the duration of the evaluation periods and the interaction of the objectives of different entities for both the vertical (hierarchic) and horizontal (individual and collective) levels.

Interlocking directorates in Spanish banking in the twentieth century

Spanish banking historiography asserts that the largest banks performed in the twentieth century as though they constituted a monopoly. One of their main coordination schemes would have been a network of interlocking bank directors that would include most of the financial firms. Evidence available for the 1920s and 1960s seems to confirm the veracity of this hypothesis. In this paper, more systematic evidence is presented to cover the whole twentieth century with the aim of checking whether these networks persisted over the entire period or they were by-products of temporary situations. Our results show that no general network remained for more than a decade. Therefore, it should be ruled out that interlocking directorates worked as a coordination device of an alleged banking cartel.

An overview of the use of neural networks for data mining tasks

In the recent years, the area of data mining has been experiencing considerable demand for technologies that extract knowledge from large and complex data sources. There has been substantial commercial interest as well as active research in the area that aim to develop new and improved approaches for extracting information, relationships, and patterns from large datasets. Artificial neural networks (NNs) are popular biologically-inspired intelligent methodologies, whose classification, prediction, and pattern recognition capabilities have been utilized successfully in many areas, including science, engineering, medicine, business, banking, telecommunication, and many other fields. This paper highlights from a data mining perspective the implementation of NN, using supervised and unsupervised learning, for pattern recognition, classification, prediction, and cluster analysis, and focuses the discussion on their usage in bioinformatics and financial data analysis tasks. © 2012 Wiley Periodicals, Inc.

Bank networks and firm credit: an agent based model approach

Starting from the idea that economic systems fall into complexity theory, where its many agents interact with each other without a central control and that these interactions are able to change the future behavior of the agents and the entire system, similar to a chaotic system we increase the model of Russo et al. (2014) to carry out three experiments focusing on the interaction between Banks and Firms in an artificial economy. The first experiment is relative to Relationship Banking where, according to the literature, the interaction over time between Banks and Firms are able to produce mutual benefits, mainly due to reduction of the information asymmetry between them. The following experiment is related to information heterogeneity in the credit market, where the larger the bank, the higher their visibility in the credit market, increasing the number of consult for new loans. Finally, the third experiment is about the effects on the credit market of the heterogeneity of prices that Firms faces in the goods market.

Contrasting Effects Of Land Use Intensity And Exotic Host Plants On The Specialization Of Interactions In Plant-herbivore Networks.

Human land use tends to decrease the diversity of native plant species and facilitate the invasion and establishment of exotic ones. Such changes in land use and plant community composition usually have negative impacts on the assemblages of native herbivorous insects. Highly specialized herbivores are expected to be especially sensitive to land use intensification and the presence of exotic plant species because they are neither capable of consuming alternative plant species of the native flora nor exotic plant species. Therefore, higher levels of land use intensity might reduce the proportion of highly specialized herbivores, which ultimately would lead to changes in the specialization of interactions in plant-herbivore networks. This study investigates the community-wide effects of land use intensity on the degree of specialization of 72 plant-herbivore networks, including effects mediated by the increase in the proportion of exotic plant species. Contrary to our expectation, the net effect of land use intensity on network specialization was positive. However, this positive effect of land use intensity was partially canceled by an opposite effect of the proportion of exotic plant species on network specialization. When we analyzed networks composed exclusively of endophagous herbivores separately from those composed exclusively of exophagous herbivores, we found that only endophages showed a consistent change in network specialization at higher land use levels. Altogether, these results indicate that land use intensity is an important ecological driver of network specialization, by way of reducing the local host range of herbivore guilds with highly specialized feeding habits. However, because the effect of land use intensity is offset by an opposite effect owing to the proportion of exotic host species, the net effect of land use in a given herbivore assemblage will likely depend on the extent of the replacement of native host species with exotic ones.

Complex networks: the key to systems biology

Though introduced recently, complex networks research has grown steadily because of its potential to represent, characterize and model a wide range of intricate natural systems and phenomena. Because of the intrinsic complexity and systemic organization of life, complex networks provide a specially promising framework for systems biology investigation. The current article is an up-to-date review of the major developments related to the application of complex networks in biology, with special attention focused on the more recent literature. The main concepts and models of complex networks are presented and illustrated in an accessible fashion. Three main types of networks are covered: transcriptional regulatory networks, protein-protein interaction networks and metabolic networks. The key role of complex networks for systems biology is extensively illustrated by several of the papers reviewed.

Neural networks and statistical analysis for classification of corneal videokeratography maps based on Zernike coefficients: a quantitative comparison

PURPOSE: The main goal of this study was to develop and compare two different techniques for classification of specific types of corneal shapes when Zernike coefficients are used as inputs. A feed-forward artificial Neural Network (NN) and discriminant analysis (DA) techniques were used. METHODS: The inputs both for the NN and DA were the first 15 standard Zernike coefficients for 80 previously classified corneal elevation data files from an Eyesys System 2000 Videokeratograph (VK), installed at the Departamento de Oftalmologia of the Escola Paulista de Medicina, São Paulo. The NN had 5 output neurons which were associated with 5 typical corneal shapes: keratoconus, with-the-rule astigmatism, against-the-rule astigmatism, "regular" or "normal" shape and post-PRK. RESULTS: The NN and DA responses were statistically analyzed in terms of precision ([true positive+true negative]/total number of cases). Mean overall results for all cases for the NN and DA techniques were, respectively, 94% and 84.8%. CONCLUSION: Although we used a relatively small database, results obtained in the present study indicate that Zernike polynomials as descriptors of corneal shape may be a reliable parameter as input data for diagnostic automation of VK maps, using either NN or DA.

Evaluation of follicular lymphoid depletion in the Bursa of Fabricius: an alternative methodology using digital image analysis and artificial neural networks

Fifty Bursa of Fabricius (BF) were examined by conventional optical microscopy and digital images were acquired and processed using Matlab® 6.5 software. The Artificial Neuronal Network (ANN) was generated using Neuroshell® Classifier software and the optical and digital data were compared. The ANN was able to make a comparable classification of digital and optical scores. The use of ANN was able to classify correctly the majority of the follicles, reaching sensibility and specificity of 89% and 96%, respectively. When the follicles were scored and grouped in a binary fashion the sensibility increased to 90% and obtained the maximum value for the specificity of 92%. These results demonstrate that the use of digital image analysis and ANN is a useful tool for the pathological classification of the BF lymphoid depletion. In addition it provides objective results that allow measuring the dimension of the error in the diagnosis and classification therefore making comparison between databases feasible.

Classification of breast masses using a committee machine of artificial neural networks

This work proposes a new approach using a committee machine of artificial neural networks to classify masses found in mammograms as benign or malignant. Three shape factors, three edge-sharpness measures, and 14 texture measures are used for the classification of 20 regions of interest (ROIs) related to malignant tumors and 37 ROIs related to benign masses. A group of multilayer perceptrons (MLPs) is employed as a committee machine of neural network classifiers. The classification results are reached by combining the responses of the individual classifiers. Experiments involving changes in the learning algorithm of the committee machine are conducted. The classification accuracy is evaluated using the area A. under the receiver operating characteristics (ROC) curve. The A, result for the committee machine is compared with the A, results obtained using MLPs and single-layer perceptrons (SLPs), as well as a linear discriminant analysis (LDA) classifier Tests are carried out using the student's t-distribution. The committee machine classifier outperforms the MLP SLP, and LDA classifiers in the following cases: with the shape measure of spiculation index, the A, values of the four methods are, in order 0.93, 0.84, 0.75, and 0.76; and with the edge-sharpness measure of acutance, the values are 0.79, 0.70, 0.69, and 0.74. Although the features with which improvement is obtained with the committee machines are not the same as those that provided the maximal value of A(z) (A(z) = 0.99 with some shape features, with or without the committee machine), they correspond to features that are not critically dependent on the accuracy of the boundaries of the masses, which is an important result. (c) 2008 SPIE and IS&T.

Fully Connected PLL Networks: How Filter Determines the Number of Nodes

Synchronization plays an important role in telecommunication systems, integrated circuits, and automation systems. Formerly, the masterslave synchronization strategy was used in the great majority of cases due to its reliability and simplicity. Recently, with the wireless networks development, and with the increase of the operation frequency of integrated circuits, the decentralized clock distribution strategies are gaining importance. Consequently, fully connected clock distribution systems with nodes composed of phase-locked loops (PLLs) appear as a convenient engineering solution. In this work, the stability of the synchronous state of these networks is studied in two relevant situations: when the node filters are first-order lag-lead low-pass or when the node filters are second-order low-pass. For first-order filters, the synchronous state of the network shows to be stable for any number of nodes. For second-order filter, there is a superior limit for the number of nodes, depending on the PLL parameters. Copyright (C) 2009 Atila Madureira Bueno et al.

A reliable measure of similarity based on dependency for short time series: an application to gene expression networks

Background: Microarray techniques have become an important tool to the investigation of genetic relationships and the assignment of different phenotypes. Since microarrays are still very expensive, most of the experiments are performed with small samples. This paper introduces a method to quantify dependency between data series composed of few sample points. The method is used to construct gene co-expression subnetworks of highly significant edges. Results: The results shown here are for an adapted subset of a Saccharomyces cerevisiae gene expression data set with low temporal resolution and poor statistics. The method reveals common transcription factors with a high confidence level and allows the construction of subnetworks with high biological relevance that reveals characteristic features of the processes driving the organism adaptations to specific environmental conditions. Conclusion: Our method allows a reliable and sophisticated analysis of microarray data even under severe constraints. The utilization of systems biology improves the biologists ability to elucidate the mechanisms underlying celular processes and to formulate new hypotheses.