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Questa ricerca, mediante la lettura ravvicinata di Kripke e di Bourdieu, rappresenta un'analisi teoretica del vincolo comunitario come condizione della regolarità dell'uso linguistico. Più precisamente, se Kripke, attraverso la lettura di Wittgenstein, presta a Bourdieu l’impianto teorico che giustifica l’impossibilità del linguaggio privato, Bourdieu, attraverso la nozione di mercato linguistico e delle leggi che lo governano, presta a Kripke – ma anche a tutti i filosofi analitici della community view –, una teoria molto più sviluppata e molto meno astratta della nozione di comunità.

In this paper, we provide a methodology suitable to identify relevant insurance companies in a systemic risk framework. To this end, we propose a complex network approach where insurers are linked to form a global interconnected system. In particular, we extend the current literature proposing an approach based on a directed weighted multilayer network. The reciprocal influence between insurers is indeed considered in each period and in subsequent periods, calibrating arc weights on the basis of specific risk measures. Hub and authority scores are then used to assess the prominence of a company in spreading and receiving risk from the others.

Prefazione a: A. Badiou, Teoria della contraddizione e altri scritti dialettici (Mimesis 2022)

In this paper, we provide a methodology suitable to identify relevant insurance companies in a systemic risk framework. To this end, we propose a complex network approach where insurers are linked to form a global interconnected system. In particular, we extend the current literature proposing an approach based on a directed weighted multilayer network. The reciprocal influence between insurers is indeed considered in each period and in subsequent periods, calibrating arc weights on the basis of specific risk measures. Hub and authority scores are then used to assess the prominence of a company in spreading and receiving risk from the others.

We analyze the multilayer architecture of the global input-output network using sectoral trade data (WIOD, 2016 release). With a focus on the mesoscale structure and related properties, our multilayer analysis takes into consideration the splitting into industry-based layers in order to catch more peculiar relationships between countries that cannot be detected from the analysis of the single-layer aggregated network. We can identify several large international communities in which some countries trade more intensively in some specific layers. However, interestingly, our results show that these clusters can restructure and evolve over time. In general, not only their internal composition changes, but the centrality rankings of the members inside are also reordered, industries from some countries diminishing their role and others from other countries growing importance. These changes in the large international clusters may reflect the outcomes and the dynamics of cooperation, partner selection and competition among industries and among countries in the global input-output network.

Background: Postoperative morbidity remains a significant problem after pancreatico-duodenectomy. The management of pancreatic stump continues to be a challenge, and many technical solutions have been developed over the years. In this study, we report the results obtained with the use of an isolated loop for pancreatico-jejunostomy in patients with soft pancreas and small pancreatic duct diameter. Methods: Clinical data of patients submitted to pancreatico-duodenectomy in a period of sixteen years (2005–2020) were extracted from a prospective database. Patients with soft pancreas, main duct diameter < 2 mm and reconstruction by pancreatico-jejunostomy on single loop or isolated loop were selected. Primary end-point was the incidence of clinically relevant fistulas in the two groups of patients. Secondary endpoint was the length of postoperative hospital stay. A propensity score matching analysis was used for the statistics. Results: Two hundred and twenty-one patients with the above characteristics were found in the database. One hundred and twelve of these received a single-loop reconstruction and 109 an isolated loop reconstruction. Incidence of clinically relevant fistulas was higher in the first group (41% vs 27%; p = 0.023). Postoperative hospital stay was significantly shorter in the second group (21 days vs 15; p < 0.001). These results were confirmed at the propensity score matching. Conclusion: In patients with soft pancreatic texture and small main duct diameter, pancreatico-jejunostomy on isolated loop is associated with a lower incidence of clinically relevant fistulas than after classic reconstruction. The duration of postoperative hospital stay was significantly reduced, with consequent reduction of cost.

Big data and the use of advanced technologies are relevant topics in the financial market. In this context, complex networks became extremely useful in describing the structure of complex financial systems. In particular, the time evolution property of the stock markets have been described by temporal networks. However, these approaches fail to consider the interactions over time between assets. To overcome this drawback, financial markets can be described by multiplex networks where the different relations between nodes can be conveniently expressed structuring the network through different layers. To catch this kind of interconnections we provide new local clustering coefficients for multiplex networks, looking at the network from different perspectives depending on the node position, as well as a global clustering coefficient for the whole network. We also prove that all the well-known expressions for clustering coefficients existing in the literature, suitably extended to the multiplex framework, may be unified into our proposal. By means of an application to the multiplex temporal financial network, based on the returns of the S&P100 assets, we show that the proposed measures prove to be effective in describing dependencies between assets over time.

In this article we deal with the problem of portfolio allocation by enhancing network theory tools. We propose the use of the correlation network dependence structure in constructing some well-known risk-based models in which the estimation of the correlation matrix is a building block in the portfolio optimization. We formulate and solve all these portfolio allocation problems using both the standard approach and the network-based approach. Moreover, in constructing the network-based portfolios we propose the use of three different estimators for the covariance matrix: the sample, the shrinkage toward constant correlation and the depth-based estimators. All the strategies under analysis are implemented on three high-dimensional portfolios having different characteristics. We find that the network-based portfolio consistently performs better and has lower risk compared to the corresponding standard portfolio in an out-of-sample perspective.

In this paper, we investigate the mesoscale structure of the World Trade Network. In this framework, a specific role is assumed by short- and long-range interactions, and hence by any suitably defined network-based distance between countries. Therefore, we identify clusters through a new procedure that exploits Estrada communicability distance and the vibrational communicability distance, which turn out to be particularly suitable for catching the inner structure of the economic network. The proposed methodology aims at finding the distance threshold that maximizes a specific quality function defined for general metric spaces. Main advantages regard the computational efficiency of the procedure as well as the possibility to inspect intercluster and intracluster properties of the resulting communities. The numerical analysis highlights peculiar relationships between countries and provides a rich set of information that can hardly be achieved within alternative clustering approaches.

This work deals with the issue of assessing the influence of a node in the entire network and in the subnetwork to which it belongs as well, adapting the classical idea of vertex centrality. We provide a general definition of relative vertex centrality measure with respect to the classical one, referred to the whole network. Specifically, we give a decomposition of the relative centrality measure by including also the relative influence of the single node with respect to a given subgraph containing it. The proposed measure of relative centrality is tested in the empirical networks generated by collecting assets of the S&P 100, focusing on two specific centrality indices: betweenness and eigenvector centrality. The analysis is performed in a time perspective, capturing the assets influence, with respect to the characteristics of the analysed measures, in both the entire network and the specific sectors to which the assets belong.

This article investigates the behaviour of the European banking system during the financial crises that occurred in the last decades. Among the various approaches for measuring systemic risk, we consider network analysis, which describes the linkages among financial institutions and their whole structure. We construct a time-varying network of the European banking system. Banks are linked to form a global interconnected system and they mutually influence one another in terms of risk. We model their reciprocal influence via a weighted and directed network, in which weights are related to risk measures that are based on equity returns. Then, we apply two network indicators to investigate the prominence of a bank in spreading and receiving risk from the others. The results enable us to capture many features of the banking system while identifying the global systemically important banks. Moreover, the results of the analysis over time show how interconnections change over periods that are characterized by various economic scenarios

Measuring robustness is a fundamental task for analysing the structure of complex networks. Indeed, several approaches to capture the robustness properties of a network have been proposed. In this paper we focus on spectral graph theory where robustness is measured by means of a graph invariant called Kirchhoff index, expressed in terms of eigenvalues of the Laplacian matrix associated to a graph. This graph metric is highly informative as a robustness indicator for several real-world networks that can be modeled as graphs. We discuss a methodology aimed at obtaining some new and tighter bounds of this graph invariant when links are added or removed. We take advantage of real analysis techniques, based on majorization theory and optimization of functions which preserve the majorization order. Applications to simulated graphs and to empirical networks generated by collecting assets of the S&P 100 show the effectiveness of our bounds, also in providing meaningful insights with respect to the results obtained in the literature.

Understanding the structure of communities in a network has a great importance in the economic analysis. Communities are indeed characterized by specific properties, that are different from those of both the individual nodes and the whole network, and they can affect various processes on the network. In the International Trade Network, community detection aims to search sets of countries (or of trade sectors) which have a high intra-cluster connectivity and a low inter-cluster connectivity. In general, exchanges among countries occur according to preferential economic relationships ranging over different sectors. In this paper, we combine community detection with specific topological indicators, such as centrality measures. As a result, a new weighted network is constructed from the original one, in which weights are determined taking into account all the topological indicators in a multi-criteria approach. To solve the resulting Clique Partitioning Problem and find homogeneous group of nations, we use a new fast algorithm, based on quick descents to a local optimal solution. The analysis allows to cluster countries by interconnections, economic power and intensity of trade, giving an important overview on the international trade patterns.

Lo studio che segue rappresenta una ricostruzione storico-filosofica di una parte del rapporto che dal 1963 al 1970 Louis Althusser e la scuola althusseriana intrattennero con Pierre Bourdieu. Nello specifico, qui mi dedicherò alla recensione di Pierre Macherey a L’amour de l’art. Les musées d’art européens et leur public, scritto da Bourdieu con Alain Darbel nel 1966. La recensione apparve nel numero 12-13 del luglio-agosto 1966 dei «Cahiers marxistes-léninistes». Nello stesso numero, un altro testo di Macherey (Les Paysans de Balzac: un texte disparate); di Roger Establet (Culture et idéologie); di Étienne Balibar (Marxisme et linguistique); il primo saggio filosofico redatto da Alain Badiou dopo la stesura dei primi due «romanzi» (L’autonomie du processus esthétique); oltre che ad alcuni documenti che stanno lì a costituire la cornice teorica di queste ricerche: c’è un testo di Stalin (À propos du marxisme en linguistique, che supporta il testo di Balibar), di Lenin (Tolstoï, miroir de la Révolution russe, il saggio in base al quale Macherey avvierà il procedimento teorico legato alla produzione letteraria) e di Mao (Interventions aux causeries sur la littérature et l’art à Yenan, che supporta il testo di Badiou).

Following pancreatoduodenectomy (PD), the modality of pancreato-enteric continuity restoration may impact on postoperative pancreatic fistula (POPF) risk. The aim of this study is to compare, among patients with soft pancreas and at moderate/high risk for POPF, the outcomes of PD with Pancreato-Gastrostomy (PG), versus Isolated Jejunal Loop Pancreato-Jejunostomy (IJL-PJ). 193 patients with a Callery Fistula Risk Score (C-FRS) ≥ 3 operated at 3 HPB Units, two performing PG and one IJL-PJ as their preferred anastomotic technique following PD (2009–2019) were included in this study (PG = 123, IJL-PJ = 70). Primary outcomes were POPF, clinically relevant (cr-)postoperative pancreatic hemorrhage (cr-PPH), delayed gastric emptying (cr-DGE), and postoperative major complications and mortality. POPF, cr-PPH, and cr-DGE occurred in 21.8%, 17.6%, and 11.4% of patients, and did not differ significantly between PG (26%, 19.5%, and 10.6%, respectively) and IJL-PJ (17.1%, 14.3%, and 12.9%, respectively; all p > 0.05) patients. Major (Dindo ≥ 3) complication and mortality rates were 26.4% and 3.3%, respectively, and did not differ significantly between PG (29.3% and 3.8%) and IJL-PJ (21.4% and 2.9) patients (p > 0.05). A faster surgical drain and nasogastric tube removal matched a significantly shorter hospitalization among IJL-PJ patients (median LOS: 18 days versus 25 days among PG patients, p < 0.001). In conclusion, IJL-PJ and PG, when performed by surgeons specialized with the concerned anastomotic technique in patients with soft pancreas and moderate/high risk for POPF, have similar results in terms of perioperative mortality and postoperative complications both overall and specific for PD.

The aim of this paper is to provide a stochastic model useful for assessing the capital requirement for demographic risk in a framework coherent with the Solvency II Directive. The model extends to the market consistent context classical methodologies developed in a local accounting framework. The random variable demographic profit, defined in literatue under local accounting principles, is indeed analysed in a Solvency II framework. We provide a unique formulation for different non-participating life insurance contracts and we prove analytically that the valuation of demographic profit can be significantly affected by the financial conditions in the market. Regarding this topic, we implement the Vašíček model to add randomness to risk-free rates. A case study has also been developed considering a portfolio of life insurance contracts. Results prove the effectiveness of the model in highlighting the main drivers of capital requirement evaluation (e.g., the volatility of both mortality rates and risk-free rates), also compared to the local GAAP framework.

This paper proposes an optimal allocation model with the main aim to minimize systemic risk related to the sovereign risk of a set of countries. The reference methodological environment is that of complex networks theory. Specifically, we consider the weighted clustering coefficient as a proxy of systemic risk, while the interconnections among countries are captured by the relationships among default probabilities of the set of countries under consideration. The selected optimization criterion is based on minimization of the mean absolute deviation. We perform empirical analyses to validate the theoretical predictions, and interpret the findings in the context of the proposed model.

In this work, we propose a measure that aims at assessing the position of a node with respect to the interconnected groups of nodes existing in a network. In particular, since the nodes of a network can be placed at different distances from cohesive groups, we extend the standard concept of clustering coefficient and provide the local l-adjacency clustering coefficient of a node i as an opportunely weighted mean of the clustering coefficients of nodes which are at distance l from i. Thus, the standard clustering coefficient is a peculiar local l-adjacency clustering coefficient for l=0. As l varies, the local l-adjacency clustering coefficient is then used to infer insights on the position of each node in the overall structure. Empirical experiments on special business networks are carried out. In particular, the analysis of air traffic networks validate the theoretical proposal and provide supporting arguments on its usefulness.

In this article we propose a novel measure of systemic risk in the context of financial networks. To this aim, we provide a definition of systemic risk which is based on the structure, developed at different levels, of clustered neighbours around the nodes of the network. The proposed measure incorporates the generalized concept of clustering coefficient of order l of a node i introduced in Cerqueti et al. (2018). Its properties are also explored in terms of systemic risk assessment. Empirical experiments on the time-varying global banking network show the effectiveness of the presented systemic risk measure and provide insights on how systemic risk has changed over the last years, also in the light of the recent financial crisis and the subsequent more stringent regulation for globally systemically important banks.