We present a study of the network of relationships among elected members of the Finnish parliamen... more We present a study of the network of relationships among elected members of the Finnish parliament, based on a quantitative analysis of initiative co-signatures, and its evolution over 16 years. To understand the structure of the parliament, we constructed a statistically validated network of members, based on the similarity between the patterns of initiatives they signed. We looked for communities within the network and characterized them in terms of members' attributes, such as electoral district and party. To gain insight on the nested structure of communities, we constructed a hierarchical tree of members from the correlation matrix. Afterwards, we studied parliament dynamics yearly, with a focus on correlations within and between parties, by also distinguishing between government and opposition. Finally, we investigated the role played by specific individuals, at a local level. In particular, whether they act as proponents who gather consensus, or as signers. Our results provide a quantitative background to current theories in political science. From a methodological point of view, our network approach has proven able to highlight both local and global features of a complex social system.
We develop a pricing model for Sovereign Contingent Convertible bonds (S-CoCo) with payment stand... more We develop a pricing model for Sovereign Contingent Convertible bonds (S-CoCo) with payment standstills triggered by a sovereign's Credit Default Swap (CDS) spread. We model CDS spread regime switching, which is prevalent during crises, as a hidden Markov process, coupled with a mean-reverting stochastic process of spread levels under fixed regimes, in order to obtain S-CoCo prices through simulation. The paper uses the pricing model in a Longstaff-Schwartz American option pricing framework to compute future state contingent S-CoCo prices for risk management. Dual trigger pricing is also discussed using the idiosyncratic CDS spread for the sovereign debt together with a broad market index. Numerical results are reported using S-CoCo designs for Greece, Italy and Germany with both the pricing and contingent pricing models.
The use of improved covariance matrix estimators as an alternative to the sample estimator is con... more The use of improved covariance matrix estimators as an alternative to the sample estimator is considered an important approach for enhancing portfolio optimization. Here we empirically compare the performance of 9 improved covariance estimation procedures by using daily returns of 90 highly capitalized US stocks for the period 1997-2007. We find that the usefulness of covariance matrix estimators strongly depends on the ratio between estimation period T and number of stocks N , on the presence or absence of short selling, and on the performance metric considered. When short selling is allowed, several estimation methods achieve a realized risk that is significantly smaller than the one obtained with the sample covariance method. This is particularly true when T /N is close to one. Moreover many estimators reduce the fraction of negative portfolio weights, while little improvement is achieved in the degree of diversification. On the contrary when short selling is not allowed and T > N , the considered methods are unable to outperform the sample covariance in terms of realized risk but can give much more diversified portfolios than the one obtained with the sample covariance. When T < N the use of the sample covariance matrix and of the pseudoinverse gives portfolios with very poor performance.
We present a weighted estimator of the covariance and correlation in bipartite complex systems wi... more We present a weighted estimator of the covariance and correlation in bipartite complex systems with a double layer of heterogeneity. The advantage provided by the weighted estimators lies in the fact that the unweighted sample covariance and correlation can be shown to possess a bias. Indeed, such a bias affects real bipartite systems, and, for example, we report its effects on two empirical systems, one social and the other biological. On the contrary, our newly proposed weighted estimators remove the bias and are better suited to describe such systems.
We show that the Kullback-Leibler distance is a good measure of the statistical uncertainty of co... more We show that the Kullback-Leibler distance is a good measure of the statistical uncertainty of correlation matrices estimated by using a finite set of data. For correlation matrices of multivariate Gaussian variables we analytically determine the expected values of the Kullback-Leibler distance of a sample correlation matrix from a reference model and we show that the expected values are known also when the specific model is unknown. We propose to make use of the Kullback-Leibler distance to estimate the information extracted from a correlation matrix by correlation filtering procedures. We also show how to use this distance to measure the stability of filtering procedures with respect to statistical uncertainty. We explain the effectiveness of our method by comparing four filtering procedures, two of them being based on spectral analysis and the other two on hierarchical clustering. We compare these techniques as applied both to simulations of factor models and empirical data. We investigate the ability of these filtering procedures in recovering the correlation matrix of models from simulations. We discuss such an ability in terms of both the heterogeneity of model parameters and the length of data series. We also show that the two spectral techniques are typically more informative about the sample correlation matrix than techniques based on hierarchical clustering, whereas the latter are more stable with respect to statistical uncertainty.
We develop a pricing model for Sovereign Contingent Convertible bonds (S-CoCo) with payment stand... more We develop a pricing model for Sovereign Contingent Convertible bonds (S-CoCo) with payment standstills triggered by a sovereign's Credit Default Swap (CDS) spread. We model CDS spread regime switching, which is prevalent during crises, as a hidden Markov process, coupled with a mean-reverting stochastic process of spread levels under fixed regimes, in order to obtain S-CoCo prices through simulation. The paper uses the pricing model in a Longstaff-Schwartz American option pricing framework to compute future state contingent S-CoCo prices for risk management. Dual trigger pricing is also discussed using the idiosyncratic CDS spread for the sovereign debt together with a broad market index. Numerical results are reported using S-CoCo designs for Greece, Italy and Germany with both the pricing and contingent pricing models.
International Journal of Critical Infrastructure Protection, Dec 1, 2014
Pipelines are responsible for the transportation of a significant portion of the U.S. energy supp... more Pipelines are responsible for the transportation of a significant portion of the U.S. energy supply. Unfortunately, pipeline failures are common and the consequences can be catastrophic. Drawing on data from the Pipeline and Hazardous Materials Safety Administration (PHMSA) that covers approximately 40,000 incidents from 1968 to 2009, this paper explores the trends, causes and consequences of natural gas and hazardous liquid pipeline accidents. The analysis indicates that fatalities and injuries from pipeline accidents are generally decreasing over time, while property damage and, in some cases, the numbers of incidents are increasing over time. In five of the ten cases considered in this paper, the damage from pipeline accidentsin terms of injuries, fatalities and volume of product spilledare well characterized by a power-law distribution, indicating that catastrophic pipeline accidents are more likely than would be predicted by more common "thin-tailed" distributions. The results also indicate that relatively few accidents account for a large share of total property damage, while smaller, single-fatality and single-injury incidents account for a large share of total fatalities and injuries (43% versus 32%, respectively).
We investigate the daily correlation present among market indices of stock exchanges located all ... more We investigate the daily correlation present among market indices of stock exchanges located all over the world in the time period Jan 1996-Jul 2009. We discover that the correlation among market indices presents both a fast and a slow dynamics. The slow dynamics reflects the development and consolidation of globalization. The fast dynamics is associated with critical events that originate in a specific country or region of the world and rapidly affect the global system. We provide evidence that the short term timescale of correlation among market indices is less than 3 trading months (about 60 trading days). The average values of the non diagonal elements of the correlation matrix, correlation based graphs and the spectral properties of the largest eigenvalues and eigenvectors of the correlation matrix are carrying information about the fast and slow dynamics of correlation of market indices. We introduce a measure of mutual information based on link co-occurrence in networks, in order to detect the fast dynamics of successive changes of correlation based graphs in a quantitative way.
AND the Multidisciplinary and Epidemiological Studies on Autism spectrum disorder (MESA) Group. S... more AND the Multidisciplinary and Epidemiological Studies on Autism spectrum disorder (MESA) Group. Summary Autism spectrum disorder (ASD) is a complex neurodevelopmental syndrome of emerging public health concern, according to a documented significant increase of diagnosed cases of ASD in Europe and USA. In Italy, actually, it is not possible to estimate at national level a reliable ASD occurrence by using existing health and scholastic data flows. The lack of information has implications on social and healthcare services dedicated to subjects affected by ADS. The database of the Italian institute in charge of social and security assistance was accessed at the provincial level to investigate the ASD cases occurred in the Palermo province. The official reports of all subjects visited in 2013 by INPS physicians were analyzed by using an automatic software and diagnosis consistent with ASD were extracted and flagged. Our findings support the choice of alternative use of INPS administrative database in order to define a reliable ASD occurrence estimate as first step to develop an integrated epidemiological surveillance system on ASD.
The shift from defined benefits (DB) to defined contributions (DC) is pervasive among pension fun... more The shift from defined benefits (DB) to defined contributions (DC) is pervasive among pension funds, due to demographic changes and macroeconomic pressures. In DB all risks are borne by the provider, while in plain vanilla DC all risks are borne by the beneficiary. For DC to provide income security some kind of guarantee is required. A minimum guarantee clause can be modeled as a put option written on some underlying reference portfolio of assets and we propose a discrete model that optimally selects the reference portfolio to minimise the cost of a guarantee. While the relation DB-DC is typically viewed as a binary one, the model setup can be used to price a wide range of guarantees creating a continuum between DB and DC. Integrating guarantee pricing with asset allocation decision is useful to both pension fund managers and regulators. The former are given a yardstick to assess if a given asset portfolio is fit-for-purpose; the latter can assess differences of specific reference funds with respect to the optimal one, signalling possible cases of moral hazard. We develop the model and report extensive numerical results to illustrate its potential uses.
Probabilistic topic models have become one of the most widespread machine learning techniques in ... more Probabilistic topic models have become one of the most widespread machine learning techniques in textual analysis. Topic discovering is an unsupervised process that does not guarantee the interpretability of its output. Hence, the automatic evaluation of topic coherence has attracted the interest of many researchers over the last decade, and it is an open research area. The present article offers a new quality evaluation method based on Statistically Validated Networks (SVNs). The proposed probabilistic approach consists of representing each topic as a weighted network of its most probable words. The presence of a link between each pair of words is assessed by statistically validating their co-occurrence in sentences against the null hypothesis of random co-occurrence. The proposed method allows one to distinguish between high-quality and low-quality topics, by making use of a battery of statistical tests. The statistically significant pairwise associations of words represented by the links in the SVN might reasonably be expected to be strictly related to the semantic coherence and interpretability of a topic. Therefore, the more connected the network, the more coherent the topic in question. We demonstrate the effectiveness of the method through an analysis of a real text corpus, which shows that the proposed measure is more correlated with human judgement than the state-of-the-art coherence measures.
The aim of the present work is to investigate the relationships established within Cosa Nostra, b... more The aim of the present work is to investigate the relationships established within Cosa Nostra, by making use of networks and complex-systems methods. The analysis is performed at three different levels, that is, individuals, groups within mafia syndicates, and relationships amongst mafia syndicates. The reported empirical analysis is based on the criminal records of 632 affiliates to Cosa Nostra selected from a set of 125 judgements emitted by the Palermo courts from 2000 to 2014. According to the criminal records of the Palermo Prosecutor Office, such a dataset includes approximately 10% of the whole population of Cosa Nostra affiliates in western Sicily. Furthermore, the vital statistics of 235 subjects sentenced for mafia crimes and the one of their relatives complemented the database that, overall, includes about 4000 subjects. Our results show that mafia syndicates are not specialized in terms of criminal activity, rather they show a strong territorial attachment and are involved in heterogeneous criminal activities. Since syndicates insist on a delimited territory, young affiliates are selected on a territorial basis according to the significance and variety of their past criminal activity. Once inside a syndicate, affiliates tend to specialize in a few criminal activities, depending on their attitudes and the needs of the organization. Finally, despite the fact that the vast majority of mafia affiliates are males, our results highlight that female subjects are crucial to form and consolidate alliances between mafia syndicates through suitable marriages.
Using the optical Stern-Gerlach model, we have recently shown that the non-local correlations bet... more Using the optical Stern-Gerlach model, we have recently shown that the non-local correlations between the internal variables of two atoms that successively interact with the field of an ideal cavity in proximity of a nodal region are affected by the atomic translational dynamics. As a consequence, there can be some difficulties in observing violation of the Bell's inequality for the atomic internal variables. These difficulties persist even if the atoms travel an antinodal region, except when the spatial wave packets are exactly centered in an antinodal point.
Interbank markets are fundamental for bank liquidity management. In this paper, we introduce a mo... more Interbank markets are fundamental for bank liquidity management. In this paper, we introduce a model of interbank trading with memory. Our model reproduces features of preferential trading patterns in the e-MID market recently empirically observed through the method of statistically validated networks. The memory mechanism is used to introduce a proxy of trust in the model. The key idea is that a lender, having lent many times to a borrower in the past, is more likely to lend to that borrower again in the future than to other borrowers, with which the lender has never (or has infrequently) interacted. The core of the model depends on only one parameter representing the initial attractiveness of all the banks as borrowers. Model outcomes and real data are compared through a variety of measures that describe the structure and properties of trading networks, including number of statistically validated links, bidirectional links, and 3-motifs. Refinements of the pairing method are also proposed, in order to capture finite memory and reciprocity in the model. The model is implemented within the Mason framework in Java. $ The authors acknowledge support from the FP7 research project CRISIS "Complexity Research Initiative for Systemic InstabilitieS". G.I. acknowledge support from the FP7 research project FOC "Forecasting Financial Crises ".
In this brief account I will describe the experiences I accrue during the three months (February-... more In this brief account I will describe the experiences I accrue during the three months (February-April 2004) that I spent in Canberra, at the Australian National University, Department of Applied Mathematics. In this department I found the ideal working environment where physicists, chemists, engineers of materials and mathematicians cooperate in studies ranging from nano-technology to early fossil dating, including the study of graphs, granular materials, complex mesoscopic phases and disordered systems.
In the optical Stern-Gerlach effect the two branches in which the incoming atomic packet splits u... more In the optical Stern-Gerlach effect the two branches in which the incoming atomic packet splits up can display interference pattern outside the cavity when a field measurement is made which erases the which-way information on the quantum paths the system can follow. On the contrary, the mere possibility to acquire this information causes a decoherence effect which cancels out the interference pattern. A phase space analysis is also carried out to investigate on the negativity of the Wigner function and on the connection between its covariance matrix and the distinguishability of the quantum paths.
We present a study of the network of relationships among elected members of the Finnish parliamen... more We present a study of the network of relationships among elected members of the Finnish parliament, based on a quantitative analysis of initiative co-signatures, and its evolution over 16 years. To understand the structure of the parliament, we constructed a statistically validated network of members, based on the similarity between the patterns of initiatives they signed. We looked for communities within the network and characterized them in terms of members' attributes, such as electoral district and party. To gain insight on the nested structure of communities, we constructed a hierarchical tree of members from the correlation matrix. Afterwards, we studied parliament dynamics yearly, with a focus on correlations within and between parties, by also distinguishing between government and opposition. Finally, we investigated the role played by specific individuals, at a local level. In particular, whether they act as proponents who gather consensus, or as signers. Our results provide a quantitative background to current theories in political science. From a methodological point of view, our network approach has proven able to highlight both local and global features of a complex social system.
We develop a pricing model for Sovereign Contingent Convertible bonds (S-CoCo) with payment stand... more We develop a pricing model for Sovereign Contingent Convertible bonds (S-CoCo) with payment standstills triggered by a sovereign's Credit Default Swap (CDS) spread. We model CDS spread regime switching, which is prevalent during crises, as a hidden Markov process, coupled with a mean-reverting stochastic process of spread levels under fixed regimes, in order to obtain S-CoCo prices through simulation. The paper uses the pricing model in a Longstaff-Schwartz American option pricing framework to compute future state contingent S-CoCo prices for risk management. Dual trigger pricing is also discussed using the idiosyncratic CDS spread for the sovereign debt together with a broad market index. Numerical results are reported using S-CoCo designs for Greece, Italy and Germany with both the pricing and contingent pricing models.
The use of improved covariance matrix estimators as an alternative to the sample estimator is con... more The use of improved covariance matrix estimators as an alternative to the sample estimator is considered an important approach for enhancing portfolio optimization. Here we empirically compare the performance of 9 improved covariance estimation procedures by using daily returns of 90 highly capitalized US stocks for the period 1997-2007. We find that the usefulness of covariance matrix estimators strongly depends on the ratio between estimation period T and number of stocks N , on the presence or absence of short selling, and on the performance metric considered. When short selling is allowed, several estimation methods achieve a realized risk that is significantly smaller than the one obtained with the sample covariance method. This is particularly true when T /N is close to one. Moreover many estimators reduce the fraction of negative portfolio weights, while little improvement is achieved in the degree of diversification. On the contrary when short selling is not allowed and T > N , the considered methods are unable to outperform the sample covariance in terms of realized risk but can give much more diversified portfolios than the one obtained with the sample covariance. When T < N the use of the sample covariance matrix and of the pseudoinverse gives portfolios with very poor performance.
We present a weighted estimator of the covariance and correlation in bipartite complex systems wi... more We present a weighted estimator of the covariance and correlation in bipartite complex systems with a double layer of heterogeneity. The advantage provided by the weighted estimators lies in the fact that the unweighted sample covariance and correlation can be shown to possess a bias. Indeed, such a bias affects real bipartite systems, and, for example, we report its effects on two empirical systems, one social and the other biological. On the contrary, our newly proposed weighted estimators remove the bias and are better suited to describe such systems.
We show that the Kullback-Leibler distance is a good measure of the statistical uncertainty of co... more We show that the Kullback-Leibler distance is a good measure of the statistical uncertainty of correlation matrices estimated by using a finite set of data. For correlation matrices of multivariate Gaussian variables we analytically determine the expected values of the Kullback-Leibler distance of a sample correlation matrix from a reference model and we show that the expected values are known also when the specific model is unknown. We propose to make use of the Kullback-Leibler distance to estimate the information extracted from a correlation matrix by correlation filtering procedures. We also show how to use this distance to measure the stability of filtering procedures with respect to statistical uncertainty. We explain the effectiveness of our method by comparing four filtering procedures, two of them being based on spectral analysis and the other two on hierarchical clustering. We compare these techniques as applied both to simulations of factor models and empirical data. We investigate the ability of these filtering procedures in recovering the correlation matrix of models from simulations. We discuss such an ability in terms of both the heterogeneity of model parameters and the length of data series. We also show that the two spectral techniques are typically more informative about the sample correlation matrix than techniques based on hierarchical clustering, whereas the latter are more stable with respect to statistical uncertainty.
We develop a pricing model for Sovereign Contingent Convertible bonds (S-CoCo) with payment stand... more We develop a pricing model for Sovereign Contingent Convertible bonds (S-CoCo) with payment standstills triggered by a sovereign's Credit Default Swap (CDS) spread. We model CDS spread regime switching, which is prevalent during crises, as a hidden Markov process, coupled with a mean-reverting stochastic process of spread levels under fixed regimes, in order to obtain S-CoCo prices through simulation. The paper uses the pricing model in a Longstaff-Schwartz American option pricing framework to compute future state contingent S-CoCo prices for risk management. Dual trigger pricing is also discussed using the idiosyncratic CDS spread for the sovereign debt together with a broad market index. Numerical results are reported using S-CoCo designs for Greece, Italy and Germany with both the pricing and contingent pricing models.
International Journal of Critical Infrastructure Protection, Dec 1, 2014
Pipelines are responsible for the transportation of a significant portion of the U.S. energy supp... more Pipelines are responsible for the transportation of a significant portion of the U.S. energy supply. Unfortunately, pipeline failures are common and the consequences can be catastrophic. Drawing on data from the Pipeline and Hazardous Materials Safety Administration (PHMSA) that covers approximately 40,000 incidents from 1968 to 2009, this paper explores the trends, causes and consequences of natural gas and hazardous liquid pipeline accidents. The analysis indicates that fatalities and injuries from pipeline accidents are generally decreasing over time, while property damage and, in some cases, the numbers of incidents are increasing over time. In five of the ten cases considered in this paper, the damage from pipeline accidentsin terms of injuries, fatalities and volume of product spilledare well characterized by a power-law distribution, indicating that catastrophic pipeline accidents are more likely than would be predicted by more common "thin-tailed" distributions. The results also indicate that relatively few accidents account for a large share of total property damage, while smaller, single-fatality and single-injury incidents account for a large share of total fatalities and injuries (43% versus 32%, respectively).
We investigate the daily correlation present among market indices of stock exchanges located all ... more We investigate the daily correlation present among market indices of stock exchanges located all over the world in the time period Jan 1996-Jul 2009. We discover that the correlation among market indices presents both a fast and a slow dynamics. The slow dynamics reflects the development and consolidation of globalization. The fast dynamics is associated with critical events that originate in a specific country or region of the world and rapidly affect the global system. We provide evidence that the short term timescale of correlation among market indices is less than 3 trading months (about 60 trading days). The average values of the non diagonal elements of the correlation matrix, correlation based graphs and the spectral properties of the largest eigenvalues and eigenvectors of the correlation matrix are carrying information about the fast and slow dynamics of correlation of market indices. We introduce a measure of mutual information based on link co-occurrence in networks, in order to detect the fast dynamics of successive changes of correlation based graphs in a quantitative way.
AND the Multidisciplinary and Epidemiological Studies on Autism spectrum disorder (MESA) Group. S... more AND the Multidisciplinary and Epidemiological Studies on Autism spectrum disorder (MESA) Group. Summary Autism spectrum disorder (ASD) is a complex neurodevelopmental syndrome of emerging public health concern, according to a documented significant increase of diagnosed cases of ASD in Europe and USA. In Italy, actually, it is not possible to estimate at national level a reliable ASD occurrence by using existing health and scholastic data flows. The lack of information has implications on social and healthcare services dedicated to subjects affected by ADS. The database of the Italian institute in charge of social and security assistance was accessed at the provincial level to investigate the ASD cases occurred in the Palermo province. The official reports of all subjects visited in 2013 by INPS physicians were analyzed by using an automatic software and diagnosis consistent with ASD were extracted and flagged. Our findings support the choice of alternative use of INPS administrative database in order to define a reliable ASD occurrence estimate as first step to develop an integrated epidemiological surveillance system on ASD.
The shift from defined benefits (DB) to defined contributions (DC) is pervasive among pension fun... more The shift from defined benefits (DB) to defined contributions (DC) is pervasive among pension funds, due to demographic changes and macroeconomic pressures. In DB all risks are borne by the provider, while in plain vanilla DC all risks are borne by the beneficiary. For DC to provide income security some kind of guarantee is required. A minimum guarantee clause can be modeled as a put option written on some underlying reference portfolio of assets and we propose a discrete model that optimally selects the reference portfolio to minimise the cost of a guarantee. While the relation DB-DC is typically viewed as a binary one, the model setup can be used to price a wide range of guarantees creating a continuum between DB and DC. Integrating guarantee pricing with asset allocation decision is useful to both pension fund managers and regulators. The former are given a yardstick to assess if a given asset portfolio is fit-for-purpose; the latter can assess differences of specific reference funds with respect to the optimal one, signalling possible cases of moral hazard. We develop the model and report extensive numerical results to illustrate its potential uses.
Probabilistic topic models have become one of the most widespread machine learning techniques in ... more Probabilistic topic models have become one of the most widespread machine learning techniques in textual analysis. Topic discovering is an unsupervised process that does not guarantee the interpretability of its output. Hence, the automatic evaluation of topic coherence has attracted the interest of many researchers over the last decade, and it is an open research area. The present article offers a new quality evaluation method based on Statistically Validated Networks (SVNs). The proposed probabilistic approach consists of representing each topic as a weighted network of its most probable words. The presence of a link between each pair of words is assessed by statistically validating their co-occurrence in sentences against the null hypothesis of random co-occurrence. The proposed method allows one to distinguish between high-quality and low-quality topics, by making use of a battery of statistical tests. The statistically significant pairwise associations of words represented by the links in the SVN might reasonably be expected to be strictly related to the semantic coherence and interpretability of a topic. Therefore, the more connected the network, the more coherent the topic in question. We demonstrate the effectiveness of the method through an analysis of a real text corpus, which shows that the proposed measure is more correlated with human judgement than the state-of-the-art coherence measures.
The aim of the present work is to investigate the relationships established within Cosa Nostra, b... more The aim of the present work is to investigate the relationships established within Cosa Nostra, by making use of networks and complex-systems methods. The analysis is performed at three different levels, that is, individuals, groups within mafia syndicates, and relationships amongst mafia syndicates. The reported empirical analysis is based on the criminal records of 632 affiliates to Cosa Nostra selected from a set of 125 judgements emitted by the Palermo courts from 2000 to 2014. According to the criminal records of the Palermo Prosecutor Office, such a dataset includes approximately 10% of the whole population of Cosa Nostra affiliates in western Sicily. Furthermore, the vital statistics of 235 subjects sentenced for mafia crimes and the one of their relatives complemented the database that, overall, includes about 4000 subjects. Our results show that mafia syndicates are not specialized in terms of criminal activity, rather they show a strong territorial attachment and are involved in heterogeneous criminal activities. Since syndicates insist on a delimited territory, young affiliates are selected on a territorial basis according to the significance and variety of their past criminal activity. Once inside a syndicate, affiliates tend to specialize in a few criminal activities, depending on their attitudes and the needs of the organization. Finally, despite the fact that the vast majority of mafia affiliates are males, our results highlight that female subjects are crucial to form and consolidate alliances between mafia syndicates through suitable marriages.
Using the optical Stern-Gerlach model, we have recently shown that the non-local correlations bet... more Using the optical Stern-Gerlach model, we have recently shown that the non-local correlations between the internal variables of two atoms that successively interact with the field of an ideal cavity in proximity of a nodal region are affected by the atomic translational dynamics. As a consequence, there can be some difficulties in observing violation of the Bell's inequality for the atomic internal variables. These difficulties persist even if the atoms travel an antinodal region, except when the spatial wave packets are exactly centered in an antinodal point.
Interbank markets are fundamental for bank liquidity management. In this paper, we introduce a mo... more Interbank markets are fundamental for bank liquidity management. In this paper, we introduce a model of interbank trading with memory. Our model reproduces features of preferential trading patterns in the e-MID market recently empirically observed through the method of statistically validated networks. The memory mechanism is used to introduce a proxy of trust in the model. The key idea is that a lender, having lent many times to a borrower in the past, is more likely to lend to that borrower again in the future than to other borrowers, with which the lender has never (or has infrequently) interacted. The core of the model depends on only one parameter representing the initial attractiveness of all the banks as borrowers. Model outcomes and real data are compared through a variety of measures that describe the structure and properties of trading networks, including number of statistically validated links, bidirectional links, and 3-motifs. Refinements of the pairing method are also proposed, in order to capture finite memory and reciprocity in the model. The model is implemented within the Mason framework in Java. $ The authors acknowledge support from the FP7 research project CRISIS "Complexity Research Initiative for Systemic InstabilitieS". G.I. acknowledge support from the FP7 research project FOC "Forecasting Financial Crises ".
In this brief account I will describe the experiences I accrue during the three months (February-... more In this brief account I will describe the experiences I accrue during the three months (February-April 2004) that I spent in Canberra, at the Australian National University, Department of Applied Mathematics. In this department I found the ideal working environment where physicists, chemists, engineers of materials and mathematicians cooperate in studies ranging from nano-technology to early fossil dating, including the study of graphs, granular materials, complex mesoscopic phases and disordered systems.
In the optical Stern-Gerlach effect the two branches in which the incoming atomic packet splits u... more In the optical Stern-Gerlach effect the two branches in which the incoming atomic packet splits up can display interference pattern outside the cavity when a field measurement is made which erases the which-way information on the quantum paths the system can follow. On the contrary, the mere possibility to acquire this information causes a decoherence effect which cancels out the interference pattern. A phase space analysis is also carried out to investigate on the negativity of the Wigner function and on the connection between its covariance matrix and the distinguishability of the quantum paths.
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Papers by Michele Tumminello