Interlinkages and structural changes in cross-border liabilities: a network approach

We study the international interbank market through a geometrical and a topological analysis of empirical data. The geometrical analysis of the time series of cross-country liabilities shows that the systematic information of the interbank international market is contained in a space of small dimension, from which a topological characterization could be conveniently carried out. Weighted and complete networks of financial linkages across countries are developed, for which continuous clustering, degree centrality and closeness centrality are computed. The behavior of these topological coefficients reveals an important modification acting in the financial linkages in the period 1997-2011. Here we show that, besides the generalized clustering increase, there is a persistent increment in the degree of connectivity and in the closeness centrality of some countries. These countries seem to correspond to critical locations where tax policies might provide opportunities to shift debts. Such critical locations highlight the role that specific countries play in the network structure and helps to situates the turbulent period that has been characterizing the global financial system since the Summer 2007 as the counterpart of a larger structural change going on for a more than one decade.Comment: 24 pages, 11 figure

Network based scoring models to improve credit risk management in peer to peer lending platforms

Financial intermediation has changed extensively over the course of the last two decades. One of the most significant change has been the emergence of FinTech. In the context of credit services, fintech peer to peer lenders have introduced many opportunities, among which improved speed, better customer experience, and reduced costs. However, peer-to-peer lending platforms lead to higher risks, among which higher credit risk: not owned by the lenders, and systemic risks: due to the high interconnectedness among borrowers generated by the platform. This calls for new and more accurate credit risk models to protect consumers and preserve financial stability. In this paper we propose to enhance credit risk accuracy of peer-to-peer platforms by leveraging topological information embedded into similarity networks, derived from borrowers' financial information. Topological coefficients describing borrowers' importance and community structures are employed as additional explanatory variables, leading to an improved predictive performance of credit scoring models

Better to stay apart: asset commonality, bipartite network centrality, and investment strategies

By exploiting a bipartite network representation of the relationships between mutual funds and portfolio holdings, we propose an indicator that we derive from the analysis of the network, labelled the Average Commonality Coefficient (ACC), which measures how frequently the assets in the fund portfolio are present in the portfolios of the other funds of the market. This indicator reflects the investment behavior of funds' managers as a function of the popularity of the assets they held. We show that $ACC$ provides useful information to discriminate between funds investing in niche markets and those investing in more popular assets. More importantly, we find that $ACC$ is able to provide indication on the performance of the funds. In particular, we find that funds investing in less popular assets generally outperform those investing in more popular financial instruments, even when correcting for standard factors. Moreover, funds with a low $ACC$ have been less affected by the 2007-08 global financial crisis, likely because less exposed to fire sales spillovers.Comment: 38 pages, 6 figure

Network based credit risk models

Peer-to-Peer lending platforms may lead to cost reduction, and to an improved user experience. These improvements may come at the price of inaccurate credit risk measurements, which can hamper lenders and endanger the stability of a financial system. In the article, we propose how to improve credit risk accuracy of peer to peer platforms and, specifically, of those who lend to small and medium enterprises. To achieve this goal, we propose toaugment traditional credit scoring methods with “alternative data” that consist of centralitymeasures derived from similarity networks among borrowers, deduced from their financialratios. Our empirical findings suggest that the proposed approach improves predictiveaccuracy as well as model explainability

Transition drivers and crisis signaling in stock markets

The present paper introduces an up-to-date methodology to detect Early Warning Signals of critical transitions, that manifest when distress stages in financial markets are about to take place. As a first step, we demonstrate that a high-dimensional dynamical system can be formulated in a simpler form but in an abstract phase space. Then we detect its approaching towards a critical transition by means of a set of observable variables that exhibit some particular statistical features. We name these variables the Leading Temporal Module. The impactful change in the properties of this group reflects the transition of the system from a normal to a distress state. Starting from these observations we develop an early warning indicator for determining the proximity of a financial crisis. The proposed measure is model free and the application to three different stock markets, together with the comparison with alternative systemic risk measures, highlights the usefulness in signaling upcoming distress phases. Computational results establish that the methodology we propose is effective and it may constitute a relevant decision support mechanism for macro prudential policies

The topology of cross-border exposures: beyond the minimal spanning tree approach

The recent financial crisis has stressed the need to understand financial systems as networks of interdependent countries, where cross-border financial linkages play the fundamental role. It has also been emphasized that the relevance of these networks relies on the representation of changes follow-on the occurrence of stress events. Adopting a topological approach we are able to address the role that network structures play in the spread of shocks and conversely, the effectiveness of stress events and its impact on the structure of the networks. Here, from series of interbank liabilities and claims over different time periods, we have developed networks of positions (net claims) between countries. Besides the Minimal Spanning Tree analysis of the time-constrained networks, a coefficient of residuality is defined to capture the structural evolution of the network of cross-border financial linkages. Because some structural changes seem to be related to the role that countries play in the financial context, networks of debtor and creditor countries are also developed. Empirical results allows to relate the network structure that emerges in the last years to the globally turbulent period that has characterized financial systems since the latest nineties. The residuality coefficient highlights an important modification acting in the financial linkages across countries in the period 1997-2011, and situates the recent financial crises as replica of a larger structural change going on since 1997.Comment: 22 pages, 8 figure

Information and Training on the Use of Telemedicine in Pediatric Population: Consensus Document of the Italian Society of Telemedicine (SIT), of the Italian Society of Preventive and Social Pediatrics (SIPPS), of the Italian Society of Pediatric Primary Care (SICuPP), of the Italian Federation of Pediatric Doctors (FIMP), and of the Syndicate of Family Pediatrician Doctors (SIMPeF)

Telemedicine has entered the daily lives of doctors, although the digital skills of healthcare professionals still remain a goal to be achieved. For the purpose of a large-scale development of telemedicine, it is necessary to create trust in the services it can offer and to favor their acceptance by healthcare professionals and patients. In this context, information for the patient regarding the use of telemedicine, the benefits that can be derived from it, and the training of healthcare professionals and patients for the use of new technologies are fundamental aspects. This consensus document is a commentary that has the aim of defining the information on and training aspects of telemedicine for pediatric patients and their caregivers, as well as pediatricians and other health professionals who deal with minors. For the present and the future of digital healthcare, there is a need for a growth in the skills of professionals and a lifelong learning approach throughout the professional life. Therefore, information and training actions are important to guarantee the necessary professionalism and knowledge of the tools, as well as a good understanding of the interactive context in which they are used. Furthermore, medical skills can also be integrated with the skills of various professionals (engineers, physicists, statisticians, and mathematicians) to birth a new category of health professionals responsible for building new semiotics, identifying criteria for predictive models to be integrated into clinical practice, standardizing clinical and research databases, and defining the boundaries of social networks and new communication technologies within health services