ID: 1511.08830

Disentangling bipartite and core-periphery structure in financial networks

November 25, 2015

View on ArXiv

Similar papers 3

The Hierarchy of Block Models

February 7, 2020

84% Match
Majid Noroozi, Marianna Pensky
Machine Learning
Machine Learning
Statistics Theory
Statistics Theory

There exist various types of network block models such as the Stochastic Block Model (SBM), the Degree Corrected Block Model (DCBM), and the Popularity Adjusted Block Model (PABM). While this leads to a variety of choices, the block models do not have a nested structure. In addition, there is a substantial jump in the number of parameters from the DCBM to the PABM. The objective of this paper is formulation of a hierarchy of block model which does not rely on arbitrary identi...

Find SimilarView on arXiv

Mixture Models and Networks -- Overview of Stochastic Blockmodelling

May 19, 2020

84% Match
Nicola Giacomo De, Benjamin Sischka, Göran Kauermann
Methodology
Applications

Mixture models are probabilistic models aimed at uncovering and representing latent subgroups within a population. In the realm of network data analysis, the latent subgroups of nodes are typically identified by their connectivity behaviour, with nodes behaving similarly belonging to the same community. In this context, mixture modelling is pursued through stochastic blockmodelling. We consider stochastic blockmodels and some of their variants and extensions from a mixture mo...

Find SimilarView on arXiv

Core-Periphery Structure in Networks

February 13, 2012

84% Match
M. Puck Rombach, Mason A. Porter, ... , Mucha Peter J.
Social and Information Netwo...
Statistical Mechanics
Physics and Society

Intermediate-scale (or `meso-scale') structures in networks have received considerable attention, as the algorithmic detection of such structures makes it possible to discover network features that are not apparent either at the local scale of nodes and edges or at the global scale of summary statistics. Numerous types of meso-scale structures can occur in networks, but investigations of such features have focused predominantly on the identification and study of community str...

Find SimilarView on arXiv

Modular Dynamics of Financial Market Networks

January 21, 2015

84% Match
Filipi N. Silva, Cesar H. Comin, Thomas K. DM. Peron, Francisco A. Rodrigues, Cheng Ye, Richard C. Wilson, ... , Costa Luciano da F.
Physics and Society
Statistical Finance

The financial market is a complex dynamical system composed of a large variety of intricate relationships between several entities, such as banks, corporations and institutions. At the heart of the system lies the stock exchange mechanism, which establishes a time-evolving network of trades among companies and individuals. Such network can be inferred through correlations between time series of companies stock prices, allowing the overall system to be characterized by techniq...

Find SimilarView on arXiv

The multiplex structure of interbank networks

November 19, 2013

84% Match
Leonardo Bargigli, Iasio Giovanni di, Luigi Infante, ... , Pierobon Federico
General Finance

The interbank market has a natural multiplex network representation. We employ a unique database of supervisory reports of Italian banks to the Banca d'Italia that includes all bilateral exposures broken down by maturity and by the secured and unsecured nature of the contract. We find that layers have different topological properties and persistence over time. The presence of a link in a layer is not a good predictor of the presence of the same link in other layers. Maximum e...

Find SimilarView on arXiv

Generative Models and Learning Algorithms for Core-Periphery Structured Graphs

October 4, 2022

84% Match
Sravanthi Gurugubelli, Sundeep Prabhakar Chepuri
Machine Learning

We consider core-periphery structured graphs, which are graphs with a group of densely and sparsely connected nodes, respectively, referred to as core and periphery nodes. The so-called core score of a node is related to the likelihood of it being a core node. In this paper, we focus on learning the core scores of a graph from its node attributes and connectivity structure. To this end, we propose two classes of probabilistic graphical models: affine and nonlinear. First, we ...

Find SimilarView on arXiv

Tackling information asymmetry in networks: a new entropy-based ranking index

October 26, 2017

84% Match
Paolo Barucca, Guido Caldarelli, Tiziano Squartini
Social and Information Netwo...
Physics and Society

Information is a valuable asset for agents in socio-economic systems, a significant part of the information being entailed into the very network of connections between agents. The different interlinkages patterns that agents establish may, in fact, lead to asymmetries in the knowledge of the network structure; since this entails a different ability of quantifying relevant systemic properties (e.g. the risk of financial contagion in a network of liabilities), agents capable of...

Find SimilarView on arXiv

Classification and estimation in the Stochastic Block Model based on the empirical degrees

October 29, 2011

84% Match
Antoine Channarond, Jean-Jacques Daudin, Stéphane Robin
Statistics Theory
Statistics Theory

The Stochastic Block Model (Holland et al., 1983) is a mixture model for heterogeneous network data. Unlike the usual statistical framework, new nodes give additional information about the previous ones in this model. Thereby the distribution of the degrees concentrates in points conditionally on the node class. We show under a mild assumption that classification, estimation and model selection can actually be achieved with no more than the empirical degree data. We provide a...

Find SimilarView on arXiv

Inference of Extreme Synchrony with an Entropy Measure on a Bipartite Network

July 20, 2012

84% Match
Aki-Hiro Sato
Data Analysis, Statistics an...
Computational Engineering, F...
Physics and Society
Risk Management

This article proposes a method to quantify the structure of a bipartite graph using a network entropy per link. The network entropy of a bipartite graph with random links is calculated both numerically and theoretically. As an application of the proposed method to analyze collective behavior, the affairs in which participants quote and trade in the foreign exchange market are quantified. The network entropy per link is found to correspond to the macroeconomic situation. A fin...

Find SimilarView on arXiv

Universality of the stochastic block model

June 11, 2018

84% Match
Jean-Gabriel Young, Guillaume St-Onge, ... , Dubé Louis J.
Physics and Society
Machine Learning

Mesoscopic pattern extraction (MPE) is the problem of finding a partition of the nodes of a complex network that maximizes some objective function. Many well-known network inference problems fall in this category, including, for instance, community detection, core-periphery identification, and imperfect graph coloring. In this paper, we show that the most popular algorithms designed to solve MPE problems can in fact be understood as special cases of the maximum likelihood for...

Find SimilarView on arXiv