124 research outputs found
Entangling credit and funding shocks in interbank markets
Credit and liquidity risks represent main channels of financial contagion for
interbank lending markets. On one hand, banks face potential losses whenever
their counterparties are under distress and thus unable to fulfill their
obligations. On the other hand, solvency constraints may force banks to recover
lost fundings by selling their illiquid assets, resulting in effective losses
in the presence of fire sales - that is, when funding shortcomings are
widespread over the market. Because of the complex structure of the network of
interbank exposures, these losses reverberate among banks and eventually get
amplified, with potentially catastrophic consequences for the whole financial
system. Building on Debt Rank [Battiston et al., 2012], in this work we define
a systemic risk metric that estimates the potential amplification of losses in
interbank markets accounting for both credit and liquidity contagion channels:
the Debt-Solvency Rank. We implement this framework on a dataset of 183
European banks that were publicly traded between 2004 and 2013, showing indeed
that liquidity spillovers substantially increase systemic risk, and thus cannot
be neglected in stress-test scenarios. We also provide additional evidence that
the interbank market was extremely fragile up to the 2008 financial crisis,
becoming slightly more robust only afterwards
Measuring quality, reputation and trust in online communities
In the Internet era the information overload and the challenge to detect
quality content has raised the issue of how to rank both resources and users in
online communities. In this paper we develop a general ranking method that can
simultaneously evaluate users' reputation and objects' quality in an iterative
procedure, and that exploits the trust relationships and social acquaintances
of users as an additional source of information. We test our method on two real
online communities, the EconoPhysics forum and the Last.fm music catalogue, and
determine how different variants of the algorithm influence the resultant
ranking. We show the benefits of considering trust relationships, and define
the form of the algorithm better apt to common situations
Investigating the interplay between fundamentals of national research systems: performance, investments and international collaborations
We discuss, at the macro-level of nations, the contribution of research
funding and rate of international collaboration to research performance, with
important implications for the science of science policy. In particular, we
cross-correlate suitable measures of these quantities with a
scientometric-based assessment of scientific success, studying both the average
performance of nations and their temporal dynamics in the space defined by
these variables during the last decade. We find significant differences among
nations in terms of efficiency in turning (financial) input into
bibliometrically measurable output, and we confirm that growth of international
collaboration positively correlate with scientific success, with significant
benefits brought by EU integration policies. Various geo-cultural clusters of
nations naturally emerge from our analysis. We critically discuss the possible
factors that potentially determine the observed patterns
Generalized Markov stability of network communities
We address the problem of community detection in networks by introducing a
general definition of Markov stability, based on the difference between the
probability fluxes of a Markov chain on the network at different time scales.
The specific implementation of the quality function and the resulting optimal
community structure thus become dependent both on the type of Markov process
and on the specific Markov times considered. For instance, if we use a natural
Markov chain dynamics and discount its stationary distribution -- that is, we
take as reference process the dynamics at infinite time -- we obtain the
standard formulation of the Markov stability. Notably, the possibility to use
finite-time transition probabilities to define the reference process naturally
allows detecting communities at different resolutions, without the need to
consider a continuous-time Markov chain in the small time limit. The main
advantage of our general formulation of Markov stability based on dynamical
flows is that we work with lumped Markov chains on network partitions, having
the same stationary distribution of the original process. In this way the form
of the quality function becomes invariant under partitioning, leading to a
self-consistent definition of community structures at different aggregation
scales
Bacterial protein interaction networks: connectivity is ruled by gene conservation, essentiality and function
Protein-protein interaction (PPI) networks are the backbone of all processes
in living cells. In this work we relate conservation, essentiality and
functional repertoire of a gene to the connectivity of the corresponding
protein in the PPI networks. Focusing on a set of 42 bacterial species with
reasonably separated evolutionary trajectories, we investigate three issues: i)
whether the distribution of connectivity values changes between PPI subnetworks
of essential and nonessential genes; ii) how gene conservation, measured both
by the evolutionary retention index (ERI) and by evolutionary pressures
(evaluated through the ratio and ENC plots) is related to the the
connectivity of the corresponding protein; iii) how PPI connectivities are
modulated by evolutionary and functional relationships, as represented by the
Clusters of Orthologous Proteins (COGs). We show that conservation,
essentiality and functional specialization of genes control in a quite
universal way the topology of the emerging bacterial PPI networks. Noteworthy,
a structural transition in the network is observed such that, for
connectivities , bacterial PPI networks are mostly populated by genes
that are conserved, essential and which, in most cases, belong to the COG
cluster J, related to ribosomal functions and to the processing of genetic
information
Numerical assessment of the percolation threshold using complement networks
Models of percolation processes on networks currently assume locally
tree-like structures at low densities, and are derived exactly only in the
thermodynamic limit. Finite size effects and the presence of short loops in
real systems however cause a deviation between the empirical percolation
threshold and its model-predicted value . Here we show the
existence of an empirical linear relation between and across a
large number of real and model networks. Such a putatively universal relation
can then be used to correct the estimated value of . We further show how
to obtain a more precise relation using the concept of the complement graph, by
investigating on the connection between the percolation threshold of a network,
, and that of its complement,
Evolutionary Network Games: Equilibria from Imitation and Best Response Dynamics
We consider games of strategic substitutes and complements on networks and introduce two evolutionary dynamics in order to refine their multiplicity of equilibria. Within mean field, we find that for the best-shot game, taken as a representative example of strategic substitutes, replicator-like dynamics does not lead to Nash equilibria, whereas it leads to a unique equilibrium for complements, represented by a coordination game. On the other hand, when the dynamics becomes more cognitively demanding, predictions are always Nash equilibria: for the best-shot game we find a reduced set of equilibria with a definite value of the fraction of contributors, whereas, for the coordination game, symmetric equilibria arise only for low or high initial fractions of cooperators. We further extend our study by considering complex topologies through heterogeneous mean field and show that the nature of the selected equilibria does not change for the best-shot game. However, for coordination games, we reveal an important difference: on infinitely large scale-free networks, cooperative equilibria arise for any value of the incentive to cooperate. Our analytical results are confirmed by numerical simulations and open the question of whether there can be dynamics that consistently leads to stringent equilibria refinements for both classes of games
Epidemics of Liquidity Shortages in Interbank Markets
Financial contagion from liquidity shocks has being recently ascribed as a
prominent driver of systemic risk in interbank lending markets. Building on
standard compartment models used in epidemics, in this work we develop an EDB
(Exposed-Distressed-Bankrupted) model for the dynamics of liquidity shocks
reverberation between banks, and validate it on electronic market for interbank
deposits data. We show that the interbank network was highly susceptible to
liquidity contagion at the beginning of the 2007/2008 global financial crisis,
and that the subsequent micro-prudential and liquidity hoarding policies
adopted by banks increased the network resilience to systemic risk---yet with
the undesired side effect of drying out liquidity from the market. We finally
show that the individual riskiness of a bank is better captured by its network
centrality than by its participation to the market, along with the currently
debated concept of "too interconnected to fail"
The Scientific Competitiveness of Nations
We use citation data of scientific articles produced by individual nations in
different scientific domains to determine the structure and efficiency of
national research systems. We characterize the scientific fitness of each
nation (that is, the competitiveness of its research system) and the complexity
of each scientific domain by means of a non-linear iterative algorithm able to
assess quantitatively the advantage of scientific diversification. We find that
technological leading nations, beyond having the largest production of
scientific papers and the largest number of citations, do not specialize in a
few scientific domains. Rather, they diversify as much as possible their
research system. On the other side, less developed nations are competitive only
in scientific domains where also many other nations are present.
Diversification thus represents the key element that correlates with scientific
and technological competitiveness. A remarkable implication of this structure
of the scientific competition is that the scientific domains playing the role
of "markers" of national scientific competitiveness are those not necessarily
of high technological requirements, but rather addressing the most
"sophisticated" needs of the society
Multiple structural transitions in interacting networks
Many real-world systems can be modeled as interconnected multilayer networks,
namely a set of networks interacting with each other. Here we present a
perturbative approach to study the properties of a general class of
interconnected networks as inter-network interactions are established. We
reveal multiple structural transitions for the algebraic connectivity of such
systems, between regimes in which each network layer keeps its independent
identity or drives diffusive processes over the whole system, thus generalizing
previous results reporting a single transition point. Furthermore we show that,
at first order in perturbation theory, the growth of the algebraic connectivity
of each layer depends only on the degree configuration of the interaction
network (projected on the respective Fiedler vector), and not on the actual
interaction topology. Our findings can have important implications in the
design of robust interconnected networked system, particularly in the presence
of network layers whose integrity is more crucial for the functioning of the
entire system. We finally show results of perturbation theory applied to the
adjacency matrix of the interconnected network, which can be useful to
characterize percolation processes on such systems
- …