49 results on '"Cerqueti R"'
Search Results
2. Influence measures in subnetworks using vertex centrality
- Author
-
Cerqueti, R, Clemente, G, Grassi, R, Cerqueti R., Clemente G. P., Grassi R., Cerqueti, R, Clemente, G, Grassi, R, Cerqueti R., Clemente G. P., and Grassi R.
- Abstract
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.
- Published
- 2020
3. Correction to: Financial interbanking networks resilience under shocks propagation (Annals of Operations Research, (2022), 10.1007/s10479-022-04567-w)
- Author
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Cerqueti, R., Cinelli, M., Ferraro, G., and Iovanella, A.
- Subjects
none - Published
- 2022
4. Data validity and statistical conformity with Benford's Law
- Author
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Cerqueti, R and Maggi, M
- Subjects
Data science Benford’s Law Lognormal distribution Statistical distance - Published
- 2021
5. An optimization model for minimizing systemic risk
- Author
-
Castellano, R, Cerqueti, R, Clemente, G, Grassi, R, Castellano, Rosella, Cerqueti, Roy, Clemente, Gian Paolo, Grassi, Rosanna, Castellano, R, Cerqueti, R, Clemente, G, Grassi, R, Castellano, Rosella, Cerqueti, Roy, Clemente, Gian Paolo, and Grassi, Rosanna
- Abstract
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.
- Published
- 2021
6. Stratified cohesiveness in complex business networks
- Author
-
Cerqueti, R, Clemente, G, Grassi, R, Cerqueti, Roy, Clemente, Gian Paolo, Grassi, Rosanna, Cerqueti, R, Clemente, G, Grassi, R, Cerqueti, Roy, Clemente, Gian Paolo, and Grassi, Rosanna
- Abstract
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.
- Published
- 2021
7. Systemic risk assessment through high order clustering coefficient
- Author
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Cerqueti, R, Clemente, G, Grassi, R, Cerqueti, Roy, Clemente, Gian Paolo, Grassi, Rosanna, Cerqueti, R, Clemente, G, Grassi, R, Cerqueti, Roy, Clemente, Gian Paolo, and Grassi, Rosanna
- Abstract
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.
- Published
- 2021
8. An optimization model for minimizing systemic risk
- Author
-
Castellano, R., Cerqueti, Roy, Clemente, Gian Paolo, Grassi, R., Cerqueti R., Clemente G. P. (ORCID:0000-0001-6795-4595), Castellano, R., Cerqueti, Roy, Clemente, Gian Paolo, Grassi, R., Cerqueti R., and Clemente G. P. (ORCID:0000-0001-6795-4595)
- Abstract
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.
- Published
- 2020
9. A Generalized Error Distribution-based method for Conditional Value-at-Risk evaluation
- Author
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Cerqueti R., Giacalone M., Panarello D., Cerqueti, R., Giacalone, M., and Panarello, D.
- Abstract
One of the most important issues in finance is to correctly measure the risk profile of a portfolio, which is fundamental to take optimal decisions on the capital allocation. In this paper, we deal with the evaluation of portfolio’s Conditional Value-at-Risk (CVaR) using a modified Gaussian Copula, where the correlation coefficient is replaced by a generalization of it, obtained as the correlation parameter ofabivariateGeneralizedErrorDistribution(G.E.D.).Wepresentanalgorithmwith the aim of verifying the performance of the G.E.D. method over the classical RiskMetrics one, resulting in higher performance of the G.E.D. method.
- Published
- 2018
10. A Network-Based Measure of the Socio-Economic Roots of the Migration Flows
- Author
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Cerqueti, R, Clemente, G, Grassi, R, Clemente, GP, Cerqueti, R, Clemente, G, Grassi, R, and Clemente, GP
- Abstract
This paper provides a unified view for defining a measure of the reasons behind migration flows whose nature is of social and economic type. To this aim, worldwide migration flows are here presented in the context of complex network and a related socio-economic indicator is conceptualized. The ingredients of the indicator also include the economic strengths of the countries and how they behave in terms of community structure, where “community” has to be intended in the sense of how countries interact in terms of immigration and emigration. Empirical analyses on a wide set of real data validate the theoretical framework, hence giving a paramount quantitative view of the roots of the worldwide migration flows.
- Published
- 2019
11. A Generalized Error Distribution-BasedMethod for Conditional Value-at-Risk Evaluation
- Author
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Cerqueti, R., Giacalone, M., Panarello, D., Corazza, M, Durban, M, Grane, A, Perna, C, and Sibillo, M
- Abstract
One of the most important issues in finance is to correctly measure the risk profile of a portfolio, which is fundamental to take optimal decisions on the capital allocation. In this paper, we deal with the evaluation of portfolio’s Conditional Value-at-Risk (CVaR) using a modified Gaussian Copula, where the correlation coefficient is replaced by a generalization of it, obtained as the correlation parameter of a bivariate Generalized Error Distribution (G.E.D.).We present an algorithm with the aim of verifying the performance of the G.E.D. method over the classical Risk- Metrics one, resulting in higher performance of the G.E.D. method.
- Published
- 2018
12. A multidisciplinary view of the financial crisis: some introductory words
- Author
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Cerqueti, R.
- Published
- 2014
13. Studies on Regional Wealth Inequalities: The Case of Italy
- Author
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Ausloos, M., primary and Cerqueti, R., additional
- Published
- 2016
- Full Text
- View/download PDF
14. On the coexistence of innovators and imitators
- Author
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Cerqueti, R, Tramontana, Fabio, Ventura, M., Tramontana, Fabio (ORCID:0000-0002-7299-5524), Cerqueti, R, Tramontana, Fabio, Ventura, M., and Tramontana, Fabio (ORCID:0000-0002-7299-5524)
- Abstract
The article develops a model laying a foundation for the idea that the relationships between competitors in the knowledge diffusion market can be described by a Lotka–Volterra system. The model can accommodate both the scenario of prey–predator and that of competition between innovators and imitators. Analytic results and numerical simulations show that a stable coexistence equilibrium is feasible under both scenarios. The work also discusses the conditions under which these results are achievable.
- Published
- 2015
15. L'evitabilità dell'estinzione di una risorsa naturale
- Author
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Cerqueti, R.
- Subjects
none - Published
- 2012
16. The Impact of Innovation on the Italian Listed Companies’ Performance
- Author
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Bartolacci, F., Castellano, N. G., and Cerqueti, R.
- Published
- 2012
17. WHY IS THE TAX EVASION SO PERSISTENT?
- Author
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Bovi, M. and Cerqueti, R.
- Subjects
Bureaucracy ,Tax evasion ,regulations - Published
- 2011
18. Light Stocks and Wealth Allocation
- Author
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Rosella Castellano and Cerqueti, R.
- Published
- 2010
19. Asymptotic solutions of a generalized eigenvalue problem
- Author
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Cerqueti, R. and Costantini, M
- Subjects
Generalized eigenvalues problem ,Weight functions ,Asymptotic convergence ,integrated process - Published
- 2009
20. A Dynamic Stochastic Asset Pricing Model with Heterogeneous Agents
- Author
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Brianzoni, S., Cerqueti, R., and Michetti, E.
- Published
- 2008
21. Risk and uncertainty in the patent race: a probabilistic model
- Author
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Cerqueti, R., primary and Ventura, M., additional
- Published
- 2013
- Full Text
- View/download PDF
22. Microeconomic modeling of financial time series with long term memory.
- Author
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Cerqueti, R. and Rotundo, G.
- Published
- 2003
- Full Text
- View/download PDF
23. Specific conjunctival challenge in polysensitized subjects
- Author
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Ciprandi, G., primary, Catrullo, A., additional, Ballestrero, A., additional, Cerqueti, R., additional, Tosca, M., additional, and Canonica, G. W., additional
- Published
- 1997
- Full Text
- View/download PDF
24. Microeconomic modeling of financial time series with long term memory
- Author
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Cerqueti, R., primary and Rotundo, G., additional
- Full Text
- View/download PDF
25. An optimization model for minimizing systemic risk
- Author
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Rosanna Grassi, Gian Paolo Clemente, Roy Cerqueti, Rosella Castellano, Castellano, R, Cerqueti, R, Clemente, G, and Grassi, R
- Subjects
Optimization ,Statistics and Probability ,Credit default swap ,Computer science ,Complex networks ,Context (language use) ,01 natural sciences ,Set (abstract data type) ,Clustering coefficient ,Mean absolute deviation ,010104 statistics & probability ,Credit default swaps ,0502 economics and business ,Systemic risk ,Econometrics ,SECS-S/06 - METODI MATEMATICI DELL'ECONOMIA E DELLE SCIENZE ATTUARIALI E FINANZIARIE ,0101 mathematics ,Proxy (statistics) ,050208 finance ,Mathematical finance ,05 social sciences ,Complex network ,Settore SECS-S/06 - METODI MATEMATICI DELL'ECONOMIA E DELLE SCIENZE ATTUARIALI E FINANZIARIE ,Statistics, Probability and Uncertainty ,Finance ,Credit risk - Abstract
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.
- Published
- 2020
26. Multiway approach for clustering time series with time varying parameters
- Author
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R. Cerqueti, R. Mattera, G. Scepi, Rosaria Lombardo, Ida Camminatiello and Violetta Simonacci, Cerqueti, R., Mattera, R., and Scepi, G.
- Subjects
Generalized Autoregressive Score (GAS), time varying parameters, Time series clustering, Spectral density, Multiway data analysis - Abstract
In this paper, we propose a new approach for clustering time series with time varying parameters. Because of the time array nature of the dataset, we adopt a multiway approach. For showing the validity of the clustering algorithm a simula- tion study is produced.
- Published
- 2022
27. Weighted score-driven fuzzy clustering of time series with a financial application
- Author
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Roy Cerqueti, Pierpaolo D’Urso, Livia De Giovanni, Massimiliano Giacalone, Raffaele Mattera, Cerqueti, R., D'Urso, P., De Giovanni, L., Giacalone, M., and Mattera, R.
- Subjects
Conditional moments ,Conditional moment ,Unconditional moments ,Artificial Intelligence ,Fuzzy clustering ,Dynamic Conditional Score ,Optimal weighting procedure for clustering ,General Engineering ,Computer Science Applications ,Conditional moments, Dynamic Conditional Score, Fuzzy clustering, Optimal weighting procedure for clustering, Unconditional moments - Abstract
Time series data are commonly clustered based on their distributional characteristics. The moments play a central role among such characteristics because of their relevant informative content. This paper aims to develop a novel approach that faces still open issues in moment-based clustering. First of all, we deal with a very general framework of time-varying moments rather than static quantities. Second, we include in the clustering model high-order moments. Third, we avoid implicit equal weighting of the considered moments by developing a clustering procedure that objectively computes the optimal weight for each moment. As a result, following a fuzzy approach, two weighted clustering models based on both unconditional and conditional moments are proposed. Since the Dynamic Conditional Score model is used to estimate both conditional and unconditional moments, the resulting framework is called weighted score-driven clustering. We apply the proposed method to financial time series as an empirical experiment.
- Published
- 2022
28. Model-based fuzzy time series clustering of conditional higher moments
- Author
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Roy Cerqueti, Massimiliano Giacalone, Raffaele Mattera, Cerqueti, R., Giacalone, M., and Mattera, R.
- Subjects
Heteroscedasticity ,Conditional moment ,Fuzzy clustering ,Time series ,Series (mathematics) ,Computer science ,Applied Mathematics ,Autocorrelation ,Probability density function ,02 engineering and technology ,Dynamic conditional score ,Fuzzy logic ,Theoretical Computer Science ,Artificial Intelligence ,020204 information systems ,Parametric model ,0202 electrical engineering, electronic engineering, information engineering ,020201 artificial intelligence & image processing ,Cluster analysis ,Algorithm ,Software - Abstract
This paper develops a new time series clustering procedure allowing for heteroskedasticity, non-normality and model's non-linearity. At this aim, we follow a fuzzy approach. Specifically, considering a Dynamic Conditional Score (DCS) model, we propose to cluster time series according to their estimated conditional moments via the Autocorrelation-based fuzzy C -means (A-FCM) algorithm. The DCS parametric modeling is appealing because of its generality and computational feasibility. The usefulness of the proposed procedure is illustrated using an experiment with simulated data and several empirical applications with financial time series assuming both linear and nonlinear models' specification and under several assumptions about time series density function.
- Published
- 2021
29. Influence measures in subnetworks using vertex centrality
- Author
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Roy Cerqueti, Rosanna Grassi, Gian Paolo Clemente, Cerqueti, R, Clemente, G, and Grassi, R
- Subjects
Vertex (graph theory) ,FOS: Computer and information sciences ,Physics - Physics and Society ,Theoretical computer science ,Computer science ,Eigenvector centrality ,Complex networks ,FOS: Physical sciences ,Physics and Society (physics.soc-ph) ,Theoretical Computer Science ,Centrality measures ,Correlation networks ,Relative centrality ,Betweenness centrality ,SECS-S/06 - METODI MATEMATICI DELL'ECONOMIA E DELLE SCIENZE ATTUARIALI E FINANZIARIE ,Subnetwork ,Social and Information Networks (cs.SI) ,Centrality measure ,Computer Science - Social and Information Networks ,Correlation network ,Complex network ,Settore SECS-S/06 - METODI MATEMATICI DELL'ECONOMIA E DELLE SCIENZE ATTUARIALI E FINANZIARIE ,Geometry and Topology ,Centrality ,Software - Abstract
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.
- Published
- 2020
30. Systemic risk assessment through high order clustering coefficient
- Author
-
Roy Cerqueti, Rosanna Grassi, Gian Paolo Clemente, Cerqueti, R, Clemente, G, and Grassi, R
- Subjects
Physics - Physics and Society ,Computer science ,Financial networks ,0211 other engineering and technologies ,Community structures ,General Decision Sciences ,FOS: Physical sciences ,Context (language use) ,02 engineering and technology ,Physics and Society (physics.soc-ph) ,Management Science and Operations Research ,FOS: Economics and business ,Systemic risk ,Econometrics ,SECS-S/06 - METODI MATEMATICI DELL'ECONOMIA E DELLE SCIENZE ATTUARIALI E FINANZIARIE ,Clustering coefficient ,Measure (data warehouse) ,Cross-border banking ,021103 operations research ,Node (networking) ,Clustering Coefficient ,Network analysi ,Settore SECS-S/06 - METODI MATEMATICI DELL'ECONOMIA E DELLE SCIENZE ATTUARIALI E FINANZIARIE ,Network analysis ,Community structure ,Financial crisis ,General Finance (q-fin.GN) ,Quantitative Finance - General Finance - Abstract
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., Submitted
- Published
- 2020
31. Rank–size distributions for banks: A cross-country analysis
- Author
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Roy Cerqueti, Filomena Pietrovito, Claudio Lupi, Alberto Franco Pozzolo, Cerqueti, R., Lupi, C., Pietrovito, F., and Pozzolo, A. F.
- Subjects
Statistics and Probability ,Bank assets ,business.industry ,Rank (computer programming) ,Bank regulation ,Distribution (economics) ,Bank asset ,Statistical and Nonlinear Physics ,Sample (statistics) ,Function (mathematics) ,Rank–size relationship ,Discount points ,Discrete Generalized Beta Distribution ,Generalized beta distribution ,Econometrics ,business ,Mathematics ,Cross country analysis - Abstract
Rank–size analysis is a powerful methodological instrument for describing the main features of a unified system by moving from an available sample of its disaggregated elements. We here study the rank–size relationship of banks’ total assets in a sample of 13 advanced economies. We show that a standard power-law function is unable to provide an adequate fit of the data, while a Discrete Generalized Beta Distribution provides a statistically satisfactory fit, being able to capture the behaviour of the distribution at low and high ranks. We then analyse the relationship between the parameters of the Discrete Generalized Beta Distribution estimated in each country and the main features of the country’s banking industry. Our results point to a connection with the degree of development of the banking sector and with some regulatory and institutional characteristics, but no relationship with riskiness.
- Published
- 2022
32. A Generalized Error Distribution Copula-based method for portfolios risk assessment
- Author
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Roy Cerqueti, Demetrio Panarello, Massimiliano Giacalone, Cerqueti, Roy, Giacalone, Massimiliano, Panarello, Demetrio, Cerqueti R., Giacalone M., and Panarello D.
- Subjects
Statistics and Probability ,Econophysics ,Correlation coefficient ,Financial risk ,Econophysic ,Generalized Error Distribution ,Statistics::Other Statistics ,Condensed Matter Physics ,01 natural sciences ,Shape parameter ,010305 fluids & plasmas ,Copula (probability theory) ,Conditional Value-at-Risk ,Expected shortfall ,Portfolio theory ,0103 physical sciences ,Econometrics ,Generalized Correlation Coefficient ,Gaussian Copula ,010306 general physics ,Generalized normal distribution ,Modern portfolio theory ,Mathematics - Abstract
In this paper, we deal with the evaluation of Conditional Value-at-Risk in the framework of portfolio theory by using a modified Gaussian Copula – where the modification is obtained by introducing the Generalized Correlation Coefficient – and by assuming a Generalized Error Distribution with properly estimated shape parameter p for the returns of the considered risky assets. In so doing, we add to the connection between standard Copula theory and financial risk assessment. A comparison analysis of our findings with those obtainable through a standard Gaussian Copula-based procedure in a set of real data is also presented.
- Published
- 2019
33. A network-based measure of the socio-economic roots of the migration flows
- Author
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Gian Paolo Clemente, Rosanna Grassi, Roy Cerqueti, Cerqueti, R, Clemente, G, and Grassi, R
- Subjects
Migration flows ,Socio-economic indicator ,Networks ,Clustering coefficient ,Sociology and Political Science ,media_common.quotation_subject ,Immigration ,050109 social psychology ,Context (language use) ,Network ,Arts and Humanities (miscellaneous) ,0502 economics and business ,Developmental and Educational Psychology ,Economics ,0501 psychology and cognitive sciences ,Economic geography ,SECS-S/06 - METODI MATEMATICI DELL'ECONOMIA E DELLE SCIENZE ATTUARIALI E FINANZIARIE ,050207 economics ,Set (psychology) ,Migration flows, socio-economic indicator, networks, clustering coefficient ,media_common ,Measure (data warehouse) ,05 social sciences ,Community structure ,General Social Sciences ,Migration flow ,Complex network ,Settore SECS-S/06 - METODI MATEMATICI DELL'ECONOMIA E DELLE SCIENZE ATTUARIALI E FINANZIARIE ,Emigration - Abstract
This paper provides a unified view for defining a measure of the reasons behind migration flows whose nature is of social and economic type. To this aim, worldwide migration flows are here presented in the context of complex network and a related socio-economic indicator is conceptualized. The ingredients of the indicator also include the economic strengths of the countries and how they behave in terms of community structure, where “community” has to be intended in the sense of how countries interact in terms of immigration and emigration. Empirical analyses on a wide set of real data validate the theoretical framework, hence giving a paramount quantitative view of the roots of the worldwide migration flows. This is a post-peer-review, pre-copyedit version of an article published in Social Indicators Research. The final authenticated version is available online at: http://dx.doi.org/10.1007/s11205-018-1883-6
- Published
- 2018
34. Improving the explainability of autoencoder factors for commodities through forecast-based Shapley values.
- Author
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Cerqueti R, Iovanella A, Mattera R, and Storani S
- Abstract
Autoencoders are dimension reduction models in the field of machine learning which can be thought of as a neural network counterpart of principal components analysis (PCA). Due to their flexibility and good performance, autoencoders have been recently used for estimating nonlinear factor models in finance. The main weakness of autoencoders is that the results are less explainable than those obtained with the PCA. In this paper, we propose the adoption of the Shapley value to improve the explainability of autoencoders in the context of nonlinear factor models. In particular, we measure the relevance of nonlinear latent factors using a forecast-based Shapley value approach that measures each latent factor's contributions in determining the out-of-sample accuracy in factor-augmented models. Considering the interesting empirical instance of the commodity market, we identify the most relevant latent factors for each commodity based on their out-of-sample forecasting ability., (© 2024. The Author(s).)
- Published
- 2024
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35. Followers do not dictate the virality of news outlets on social media.
- Author
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Sangiorgio E, Cinelli M, Cerqueti R, and Quattrociocchi W
- Abstract
Initially conceived for entertainment, social media platforms have profoundly transformed the dissemination of information and consequently reshaped the dynamics of agenda-setting. In this scenario, understanding the factors that capture audience attention and drive viral content is crucial. Employing Gibrat's Law, which posits that an entity's growth rate is unrelated to its size, we examine the engagement growth dynamics of news outlets on social media. Our analysis includes the Facebook historical data of over a thousand news outlets, encompassing approximately 57 million posts in four European languages from 2008 to the end of 2022. We discover universal growth dynamics according to which news virality is independent of the traditional size of the outlet. Moreover, our analysis reveals a significant long-term impact of news source reliability on engagement growth, with engagement induced by unreliable sources decreasing over time. We conclude the article by presenting a statistical model replicating the observed growth dynamics., (© The Author(s) 2024. Published by Oxford University Press on behalf of National Academy of Sciences.)
- Published
- 2024
- Full Text
- View/download PDF
36. Clustering networked funded European research activities through rank-size laws.
- Author
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Cerqueti R, Iovanella A, and Mattera R
- Abstract
This paper treats a well-established public evaluation problem, which is the analysis of the funded research projects. We specifically deal with the collection of the research actions funded by the European Union over the 7th Framework Programme for Research and Technological Development and Horizon 2020. The reference period is 2007-2020. The study is developed through three methodological steps. First, we consider the networked scientific institutions by stating a link between two organizations when they are partners in the same funded project. In doing so, we build yearly complex networks. We compute four nodal centrality measures with relevant, informative content for each of them. Second, we implement a rank-size procedure on each network and each centrality measure by testing four meaningful classes of parametric curves to fit the ranked data. At the end of such a step, we derive the best fit curve and the calibrated parameters. Third, we perform a clustering procedure based on the best-fit curves of the ranked data for identifying regularities and deviations among years of research and scientific institutions. The joint employment of the three methodological approaches allows a clear view of the research activity in Europe in recent years., Competing Interests: Conflict of interestThe authors declare to have no conflict of interest., (© The Author(s) 2023.)
- Published
- 2023
- Full Text
- View/download PDF
37. Multiway clustering with time-varying parameters.
- Author
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Cerqueti R, Mattera R, and Scepi G
- Abstract
This paper proposes a clustering approach for multivariate time series with time-varying parameters in a multiway framework. Although clustering techniques based on time series distribution characteristics have been extensively studied, methods based on time-varying parameters have only recently been explored and are missing for multivariate time series. This paper fills the gap by proposing a multiway approach for distribution-based clustering of multivariate time series. To show the validity of the proposed clustering procedure, we provide both a simulation study and an application to real air quality time series data., (© The Author(s) 2022.)
- Published
- 2022
- Full Text
- View/download PDF
38. The complex interplay between COVID-19 and economic activity.
- Author
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Cerqueti R, Tramontana F, and Ventura M
- Abstract
We introduce a dynamical system to model the complex interaction between COVID-19 and economic activity. The model introduces some novelties not accounted by SIR-like models. The equilibrium of the system is an unstable focus, with fluctuations having increasing size and periodicity. Numerical simulations of the model produce waves which reproduce the pandemic dynamics. In observing the stylized facts linking economics and pandemic and stating related reasonable assumptions, we obtain a Lotka-Volterra co-dynamics. This outcome is confirmed by extensive simulations. The outcomes obtained qualitatively replicate some important stylized facts deepening the knowledge about the role of some parameters in their origin and eventually in their shaping., (© 2022 Elsevier B.V. All rights reserved.)
- Published
- 2022
- Full Text
- View/download PDF
39. Combining rank-size and k-means for clustering countries over the COVID-19 new deaths per million.
- Author
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Cerqueti R and Ficcadenti V
- Abstract
This paper deals with the cluster analysis of selected countries based on COVID-19 new deaths per million data. We implement a statistical procedure that combines a rank-size exploration and a k -means approach for clustering. Specifically, we first carry out a best-fit exercise on a suitable polynomial rank-size law at an individual country level; then, we cluster the considered countries by adopting a k -means clustering procedure based on the calibrated best-fit parameters. The investigated countries are selected considering those with a high value for the Healthcare Access and Quality Index to make a consistent analysis and reduce biases from the data collection phase. Interesting results emerge from the meaningful interpretation of the parameters of the best-fit curves; in particular, we show some relevant properties of the considered countries when dealing with the days with the highest number of new daily deaths per million and waves. Moreover, the exploration of the obtained clusters allows explaining some common countries' features., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2022 Elsevier Ltd. All rights reserved.)
- Published
- 2022
- Full Text
- View/download PDF
40. Financial interbanking networks resilience under shocks propagation.
- Author
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Cerqueti R, Cinelli M, Ferraro G, and Iovanella A
- Abstract
The concept of resilience-i.e., the ability of a unified structure to absorb shocks-is of high relevance in the context of network modelling and analysis, mainly when referred to finance. This paper starts from this premise, and deals with the resilience of a financial interbanking system. At this aim, we firstly introduce a new measure of the resilience of a network, by taking into full consideration the influence of the topology of the network and the weights of its links in the shocks propagation; then, we build one financial network model related to the quarterly-based interbanking sector, whose weights are calibrated on high quality empirical data; lastly, we compute the resilience measure of the considered networks. A discussion of the results is provided, by considering both finance and network theory perspectives., (© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022.)
- Published
- 2022
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- View/download PDF
41. Outdoor light pollution and COVID-19: The Italian case.
- Author
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Argentiero A, Cerqueti R, and Maggi M
- Abstract
There is a wide debate on the connections between pollution and COVID-19 propagation. This note faces this problem by exploring the peculiar case of the correlation between outdoor light pollution and the ratio between infected people and population. We discuss the empirical case of Italian provinces (NUTS-3 level), which represent an interesting context for the noticeable entity of contagions and for the relevant level of outdoor light pollution. The empirical results, based on a multivariate cross section model controlling for income, density, population ageing and environmental pollution, show that there is a positive relation between outdoor light pollution per capita and the strength of COVID-19 infection. This effect is statistically more robust in a non linear specification than in a linear one. We interpret our findings as a piece of evidence related to the impact of outdoor light pollution on human health, thus suggesting policies aimed at reducing this important source of pollution., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2021 Elsevier Inc. All rights reserved.)
- Published
- 2021
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42. Municipal waste management: A complex network approach with an application to Italy.
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Cerqueti R, Cinelli M, and Minervini LF
- Subjects
- Cities, Italy, Solid Waste analysis, Refuse Disposal, Waste Management
- Abstract
The paper contributes to the debate concerning the management of municipal solid waste by providing an analysis of two key aspects of waste management - namely, waste separation and dispatch to treatment plants. Our analysis aims at detecting the extent to which actual behavior in (close-by) municipalities is similar with respect to those two aspects. To pursue our scope, a complex network approach is followed. In particular, we conceptualize, explore and compare two networks, whose nodes are the municipalities, while weights synthesize in one network the percentage of sorted waste that is collected at a municipal level, and in the other one the distance from the waste processing plants used by each municipality. The theoretical network models are implemented through an empirical study based on a high quality dataset referred to Italian municipalities. In this regard, the detection of communities of municipalities and their geospatial contextualization are introduced as devices for a complete description of current practices of municipal waste separation and transfers in Italy., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier Ltd. All rights reserved.)
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- 2021
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43. Predicting future cancer burden in the United States by artificial neural networks.
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Piva F, Tartari F, Giulietti M, Aiello MM, Cheng L, Lopez-Beltran A, Mazzucchelli R, Cimadamore A, Cerqueti R, Battelli N, Montironi R, and Santoni M
- Subjects
- History, 20th Century, History, 21st Century, Humans, Incidence, Neoplasms history, Neural Networks, Computer, Public Health Surveillance, United States epidemiology, Neoplasms epidemiology
- Abstract
Aims: To capture the complex relationships between risk factors and cancer incidences in the US and predict future cancer burden. Materials & methods: Two artificial neural network (ANN) algorithms were adopted: a multilayer feed-forward network (MLFFNN) and a nonlinear autoregressive network with eXogenous inputs (NARX). Data on the incidence of the four most common tumors (breast, colorectal, lung and prostate) from 1992 to 2016 (available from National Cancer Institute online datasets) were used for training and validation, and data until 2050 were predicted. Results: The rapid decreasing trend of prostate cancer incidence started in 2010 will continue until 2018-2019; it will then slow down and reach a plateau after 2050, with several differences among ethnicities. The incidence of breast cancer will reach a plateau in 2030, whereas colorectal cancer incidence will reach a minimum value of 35 per 100,000 in 2030. As for lung cancer, the incidence will decrease from 50 per 100,000 (2017) to 31 per 100,000 in 2030 and 26 per 100,000 in 2050. Conclusion: This up-to-date prediction of cancer burden in the US could be a crucial resource for planning and evaluation of cancer-control programs.
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- 2021
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44. Tsallis Entropy for Cross-Shareholding Network Configurations.
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Cerqueti R, Rotundo G, and Ausloos M
- Abstract
In this work, we develop the Tsallis entropy approach for examining the cross-shareholding network of companies traded on the Italian stock market. In such a network, the nodes represent the companies, and the links represent the ownership. Within this context, we introduce the out-degree of the nodes-which represents the diversification-and the in-degree of them-capturing the integration. Diversification and integration allow a clear description of the industrial structure that were formed by the considered companies. The stochastic dependence of diversification and integration is modeled through copulas. We argue that copulas are well suited for modelling the joint distribution. The analysis of the stochastic dependence between integration and diversification by means of the Tsallis entropy gives a crucial information on the reaction of the market structure to the external shocks-on the basis of some relevant cases of dependence between the considered variables. In this respect, the considered entropy framework provides insights on the relationship between in-degree and out-degree dependence structure and market polarisation or fairness. Moreover, the interpretation of the results in the light of the Tsallis entropy parameter gives relevant suggestions for policymakers who aim at shaping the industrial context for having high polarisation or fair joint distribution of diversification and integration. Furthermore, a discussion of possible parametrisations of the in-degree and out-degree marginal distribution-by means of power laws or exponential functions- is also carried out. An empirical experiment on a large dataset of Italian companies validates the theoretical framework.
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- 2020
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45. Genitourinary Tumors: Update on Molecular Biomarkers for Diagnosis, Prognosis and Prediction of Response to Therapy.
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Cimadamore A, Scarpelli M, Santoni M, Massari F, Tartari F, Cerqueti R, Lopez-Beltran A, Cheng L, and Montironi R
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- Humans, Antineoplastic Agents therapeutic use, Biomarkers, Tumor metabolism, Urogenital Neoplasms drug therapy, Urogenital Neoplasms metabolism
- Abstract
Background: Research of biomarkers in genitourinary tumors goes along with the development of complex emerging techniques ranging from next generation sequencing platforms, applied to archival pathology specimens, cytological samples, liquid biopsies, and to patient-derived tumor models., Methods: This contribution is an update on molecular biomarkers for diagnosis, prognosis and prediction of response to therapy in genitourinary tumors. The following major topics are dealt with: Immunological biomarkers, including the microbiome, and their potential role and caveats in renal cell carcinoma, bladder and prostate cancers and testicular germ cell tumors; Tissue biomarkers for imaging and therapy, with emphasis on Prostate-specific membrane antigen in prostate cancer; Liquid biomarkers in prostate cancer, including circulating tumor cell isolation and characterization in renal cell carcinoma, bladder cancer with emphasis on biomarkers detectable in the urine and testicular germ cell tumors; and Biomarkers and economic sustainability., Conclusion: The identification of effective biomarkers has become a major focus in cancer research, mainly due to the necessity of selecting potentially responsive patients in order to improve their outcomes, as well as to reduce the toxicity and costs related to ineffective treatments., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)
- Published
- 2019
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46. Data on the annual aggregated income taxes of the Italian municipalities over the quinquennium 2007-2011.
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Ausloos M, Cerqueti R, and Mir TA
- Abstract
This dataset contains the annual aggregated income taxes of all the Italian municipalities over the years 2007-2011. Data are clustered over the Italian regions and provinces. The source of the data is the Italian Ministry of Economics and Finance. The administrative variations in Italy over the quinquennium have been taken into account. Data are useful to understand the economic structure of Italy at the microscopic level of municipalities. They can serve also for making comparisons between economical aspects and other features of the Italian cities.
- Published
- 2018
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47. Investigating the Configurations in Cross-Shareholding: A Joint Copula-Entropy Approach.
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Cerqueti R, Rotundo G, and Ausloos M
- Abstract
The complex nature of the interlacement of economic actors is quite evident at the level of the Stock market, where any company may actually interact with the other companies buying and selling their shares. In this respect, the companies populating a Stock market, along with their connections, can be effectively modeled through a directed network, where the nodes represent the companies, and the links indicate the ownership. This paper deals with this theme and discusses the concentration of a market. A cross-shareholding matrix is considered, along with two key factors: the node out-degree distribution which represents the diversification of investments in terms of the number of involved companies, and the node in-degree distribution which reports the integration of a company due to the sales of its own shares to other companies. While diversification is widely explored in the literature, integration is most present in literature on contagions. This paper captures such quantities of interest in the two frameworks and studies the stochastic dependence of diversification and integration through a copula approach. We adopt entropies as measures for assessing the concentration in the market. The main question is to assess the dependence structure leading to a better description of the data or to market polarization (minimal entropy) or market fairness (maximal entropy). In so doing, we derive information on the way in which the in- and out-degrees should be connected in order to shape the market. The question is of interest to regulators bodies, as witnessed by specific alert threshold published on the US mergers guidelines for limiting the possibility of acquisitions and the prevalence of a single company on the market. Indeed, all countries and the EU have also rules or guidelines in order to limit concentrations, in a country or across borders, respectively. The calibration of copulas and model parameters on the basis of real data serves as an illustrative application of the theoretical proposal., Competing Interests: The authors declare no conflict of interest.
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- 2018
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48. Assessing the relationship between toxicity and economic cost of oncological target agents: A systematic review of clinical trials.
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Tartari F, Conti A, and Cerqueti R
- Subjects
- Antineoplastic Agents adverse effects, Antineoplastic Agents economics, Antineoplastic Agents therapeutic use, Cluster Analysis, Humans, Neoplasms economics, Clinical Trials as Topic, Drug Costs, Neoplasms therapy
- Abstract
Target agents are peculiar oncological drugs which differ from the traditional therapies in their ability of recognizing specific molecules expressed by tumor cells and microenvironment. Thus, their toxicity is generally lower than that associated to chemotherapy, and they represent nowadays a new standard of care in a number of tumors. This paper deals with the relationship between economic costs and toxicity of target agents. At this aim, a cluster analysis-based exploration of the main features of a large collection of them is carried out, with a specific focus on the variables leading to the identification of their toxicity and related costs. The analysis of the toxicity is based on the Severe Adverse Events (SAE) and Discontinuation (D) rates of each target agent considering data published on PubMed from 1965 to 2016 in the phase II and III studies that have led to the approval of these drugs for cancer patients by US Food and Drug Administration. The construction of the dataset represents a key step of the research, and is grounded on the critical analysis of a wide set of clinical studies. In order to capture different evaluation strategies of the toxicity, clustering is performed according to three different criteria (including Voronoi tessellation). Our procedure allows us to identify 5 different groups of target agents pooled by similar SAE and D rates and, at the same time, 3 groups based on target agents' costs for 1 month and for the median whole duration of therapy. Results highlight several specific regularities for toxicity and costs. This study present several limitations, being realized starting from clinical trials and not from individual patients' data. However, a macroscopic perspective suggests that costs are rather heterogeneous, and they do not clearly follow the clustering based on SAE and D rates.
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- 2017
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49. A Universal Rank-Size Law.
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Ausloos M and Cerqueti R
- Subjects
- Entropy, Models, Theoretical, Physics
- Abstract
A mere hyperbolic law, like the Zipf's law power function, is often inadequate to describe rank-size relationships. An alternative theoretical distribution is proposed based on theoretical physics arguments starting from the Yule-Simon distribution. A modeling is proposed leading to a universal form. A theoretical suggestion for the "best (or optimal) distribution", is provided through an entropy argument. The ranking of areas through the number of cities in various countries and some sport competition ranking serves for the present illustrations., Competing Interests: The authors have declared that no competing interests exist.
- Published
- 2016
- Full Text
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