[Show abstract][Hide abstract] ABSTRACT: We present an analysis of the credit market of Japan. The analysis is
performed by investigating the bipartite network of banks and firms which is
obtained by setting a link between a bank and a firm when a credit relationship
is present in a given time window. In our investigation we focus on a community
detection algorithm which is identifying communities composed by both banks and
firms. We show that the clusters obtained by directly working on the bipartite
network carry information about the networked nature of the Japanese credit
market. Our analysis is performed for each calendar year during the time period
from 1980 to 2011. Specifically, we obtain communities of banks and networks
for each of the 32 investigated years, and we introduce a method to track the
time evolution of these communities on a statistical basis. We then
characterize communities by detecting the simultaneous over-expression of
attributes of firms and banks. Specifically, we consider as attributes the
economic sector and the geographical location of firms and the type of banks.
In our 32 year long analysis we detect a persistence of the over-expression of
attributes of clusters of banks and firms together with a slow dynamics of
changes from some specific attributes to new ones. Our empirical observations
show that the credit market in Japan is a networked market where the type of
banks, geographical location of firms and banks and economic sector of the firm
play a role in shaping the credit relationships between banks and firms.
[Show abstract][Hide abstract] ABSTRACT: We have analyzed the Indices of Industrial Production (Seasonal Adjustment
Index) for a long period of 240 months (January 1988 to December 2007) to
develop a deeper understanding of the economic shocks. The angular frequencies
estimated using the Hilbert transformation, are almost identical for the 16
industrial sectors. Moreover, the partial phase locking was observed for the 16
sectors. These are the direct evidence of the synchronization in the Japanese
business cycle. We also showed that the information of the economic shock is
carried by the phase time-series. The common shock and individual shocks are
separated using phase time-series. The former dominates the economic shock in
all of 1992, 1998 and 2001. The obtained results suggest that the business
cycle may be described as a dynamics of the coupled limit-cycle oscillators
exposed to the common shocks and random individual shocks.
[Show abstract][Hide abstract] ABSTRACT: We construct a theoretical model for equilibrium distribution of workers
across sectors with different labor productivity, assuming that a sector can
accommodate a limited number of workers which depends only on its productivity.
A general formula for such distribution of productivity is obtained, using the
detail-balance condition necessary for equilibrium in the Ehrenfest-Brillouin
model. We also carry out an empirical analysis on the average number of workers
in given productivity sectors on the basis of an exhaustive dataset in Japan.
The theoretical formula succeeds in explaining the two distinctive
observational facts in a unified way, that is, a Boltzmann distribution with
negative temperature on low-to-medium productivity side and a decreasing part
in a power-law form on high productivity side.
[Show abstract][Hide abstract] ABSTRACT: The electronic band calculations of noble metal halides are studied to make the high ionic conducting origin of silver and cupper ions clear using the tight-binding method. The d bands of Ag ions are much more weakly coupled with the p bands of halogen ions, while those of Cu ions are much more strongly coupled with the p bands. The strength of p-d hybridization is discussed to connect with the activation energy for the ionic conduction. It is shown that the high ionic conductivity of AgX primary stems from combination of the deformability of the d shell and the weakness of the p-d hybridization.
International Journal of Modern Physics B 01/2012; 15(06n07). · 0.46 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: We investigate a Japanese transaction network consisting ofabout 800
thousand firms (nodes) and four million business relations (links) with
focus on its modular structure. Communities detected by maximizing
modularity often are dominated by firms with common features or
behaviors in the network, such as characterized by regions or industry
sectors. However, it is well known that the modularity optimization
approach has a resolution limit problem, that is, it fails in
identifying fine communities buried in large communities. To unfold such
hidden structures, we apply the community detection to each of
subnetworks formed by isolating those communities from the whole body.
Subcommunities thus identified are composed of firms with finer regions,
more specified sectors or business affiliations. Also we introduce a new
idea of reduced modularity matrix to measure the strength of relations
Progress of Theoretical Physics Supplement 01/2012; · 1.25 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: We approach the correlation structure in the Tokyo Stock Exchange (TSE)
market through a concept of community of network. To construct a
network, the correlation matrix of stock price changes, purified by
random matrix theory, is regarded as an adjacency matrix. The stock
correlation network thus constructed has negatively weighted links as
well as positively weighted links. By extracting groups in which stocks
are mainly interconnected by positive links, we find that the stocks
decomposed into four comoving groups forming communities, three of which
are strongly anticorrelated to each other, and the remainder is
comparatively neutral to the rest of the communities. The conflicting
triangle relationship between communities may cause complicated behavior
in a well-development market such as TSE. Additionally, it is observed
that some industrial sectors form distinctive coherent groups and others
are separated to competing communities.
Progress of Theoretical Physics Supplement 01/2012; · 1.25 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: We report the numerical calculations of the maximal eigenvalue for
random correlation matrices which contain autocorrelations in data. Here
the AR(1) model is adopted for such a study, we work out an empirical
formula for autocorrelation correction of the maximal eigenvalue, which
are accurate in a wide range of parameters. As an application of this
formula, we propose a criterion to single out statistically meaningful
correlations in the principal component analysis. The new criterion
within the AR(1) model incorporates autocorrelation effects into the
current method based on the random matrix theory.
Progress of Theoretical Physics Supplement 01/2012; · 1.25 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: The sectoral synchronization observed for the Japanese business cycle in the
Indices of Industrial Production data is an example of synchronization. The
stability of this synchronization under a shock, e.g., fluctuation of supply or
demand, is a matter of interest in physics and economics. We consider an
economic system made up of industry sectors and goods markets in order to
analyze the sectoral synchronization observed for the Japanese business cycle.
A coupled oscillator model that exhibits synchronization is developed based on
the Kuramoto model with inertia by adding goods markets, and analytic solutions
of the stationary state and the coupling strength are obtained. We simulate the
effects on synchronization of a sectoral shock for systems with different price
elasticities and the coupling strengths. Synchronization is reproduced as an
equilibrium solution in a nearest neighbor graph. Analysis of the order
parameters shows that the synchronization is stable for a finite elasticity,
whereas the synchronization is broken and the oscillators behave like a giant
oscillator with a certain frequency additional to the common frequency for zero
Progress of Theoretical Physics Supplement 10/2011; · 1.25 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: In this study, the fluctuation-dissipation theory is invoked to shed light on input-output interindustrial relations at a macroscopic level by its application to indices of industrial production (IIP) data for Japan. Statistical noise arising from finiteness of the time series data is carefully removed by making use of the random matrix theory in an eigenvalue analysis of the correlation matrix; as a result, two dominant eigenmodes are detected. Our previous study successfully used these two modes to demonstrate the existence of intrinsic business cycles. Here a correlation matrix constructed from the two modes describes genuine interindustrial correlations in a statistically meaningful way. Furthermore, it enables us to quantitatively discuss the relationship between shipments of final demand goods and production of intermediate goods in a linear response framework. We also investigate distinctive external stimuli for the Japanese economy exerted by the current global economic crisis. These stimuli are derived from residuals of moving-average fluctuations of the IIP remaining after subtracting the long-period components arising from inherent business cycles. The observation reveals that the fluctuation-dissipation theory is applicable to an economic system that is supposed to be far from physical equilibrium.
[Show abstract][Hide abstract] ABSTRACT: The electronic orbitals localized in the vicinity of a vacancy in a silicon crystal are calculated by an ab initio method based on the density functional theory and analyzed in association with the elastic softening observed by the recent ultrasonic experiments, especially focused on an estimate of the electric quadrupole moments. The localized orbitals due to the existence of a vacancy show largely extended properties and the quadrupole moments calculated from the orbitals indicate the strong dependence on cell sizes up to 511 atoms in the basic cell. Asymptotic values of the quadrupole moments in the limit of large size are obtained by an extrapolating method. It is shown that the quadrupole moments are enhanced due to the extension of the orbitals and the ratio of the quadrupole moments of Γ5 and Γ3 symmetries agrees well with the value deduced from the experimental results.
Solid State Communications 01/2011; 151(21):1605-1608. · 1.53 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Heterogeneity of economic agents is emphasized in a new trend of macroeconomics. Accordingly the new emerging discipline requires one to replace the production function, one of key ideas in the conven-tional economics, by an alternative which can take an explicit account of distribution of firms' production activities. In this paper we propose a new idea referred to as production copula; a copula is an analytic means for modeling dependence among variables. Such a production copula predicts value added yielded by firms with given capital and labor in a probabilistic way. It is thereby in sharp contrast to the pro-duction function where the output of firms is completely deterministic. We demonstrate empirical construction of a production copula using financial data of listed firms in Japan. Analysis of the data shows that there are significant correlations among their capital, labor and value added and confirms that the values added are too widely scattered to be represented by a production function. We employ four models for the production copula, that is, trivariate versions of Frank, Gumbel and survival Clayton and non-exchangeable trivariate Gumbel; the last one works best.
[Show abstract][Hide abstract] ABSTRACT: We shed light on industrial structure of the economic system in Japan by combining visualization technique and community analysis in this and an accompanying paper. Here we focus on visualization of a production network comprising submillion nodes (firms) and three million links (transaction relations). A network structure is optimized through molecular dynamics simulation with a spring-electrical model in a three-dimensional space. The lowest-energy state in the model, corresponding to a crystalline state in a physical system, is expected to give a comprehensible view on the network. Then we discuss how firms are distributed in the optimized network structure by classifying them according to sectors, sizes or regions. The distributions of firms reflect characteristics of individual classifications. Also propagation of the shock due to a recent economic scandal over the network is visualized.
Journal of Physics Conference Series 06/2010; 221(1):012013.
[Show abstract][Hide abstract] ABSTRACT: We present a new approach to understanding credit relationships between commercial banks and quoted firms, and with this approach, examine the temporal change in the structure of the Japanese credit network from 1980 to 2005. At each year, the credit network is regarded as a weighted bipartite graph where edges correspond to the relationships and weights refer to the amounts of loans. Reduction in the supply of credit affects firms as debtor, and failure of a firm influences banks as creditor. To quantify the dependency and influence between banks and firms, we propose a set of scores of banks and firms, which can be calculated by solving an eigenvalue problem determined by the weight of the credit network. We found that a few largest eigenvalues and corresponding eigenvectors are significant by using a null hypothesis of random bipartite graphs, and that the scores can quantitatively describe the stability or fragility of the credit network during the 25 years.
[Show abstract][Hide abstract] ABSTRACT: Research activities of Kyoto Econophysics Group is reviewed. Strong emphasis has been placed on real economy. While the initial stage of research was a first high-definition data analysis on personal income, it soon progressed to firm dynamics, growth rate distribution and establishment of Pareto's law and Gibrat's law. It then led to analysis and simulation of firm dynamics on economic network. Currently it covers a wide rage of dynamics of firms and financial institutions on complex network, using Japanese large-scale network data, some of which are not available in other countries. Activities of this group for publicising and promoting understanding of econophysics is also reviewed.
[Show abstract][Hide abstract] ABSTRACT: Econophysics is an emerging interdisciplinary field that takes advantage of the concepts and methods of statistical physics to analyse economic phenomena. This book, first published in 2010, expands the explanatory scope of econophysics to the real economy by using methods from statistical physics to analyse the success and failure of companies. Using large data sets of companies and income-earners in Japan and Europe, a distinguished team of researchers show how these methods allow us to analyse companies, from huge corporations to small firms, as heterogeneous agents interacting at multiple layers of complex networks. They then show how successful this approach is in explaining a wide range of recent findings relating to the dynamics of companies. With mathematics kept to a minimum, the book is not only a lively introduction to the field of econophysics but also provides fresh insights into company behaviour.
[Show abstract][Hide abstract] ABSTRACT: We analyze a transaction network of about 800 thousand Japanese firms to elucidate its community structure. Finding community in networks means the appearance of dense connected groups of vertices and sparse connections between groups. We adopt modularity as a quality function of communities introduced by Newman. The modularity optimization is one of effective approaches to find community. We first use a bottom-up algorithm, which makes the optimization fast by using a greedy algorithm. For the community extraction, the greedy algorithm is widely used, however, may not sufficiently optimize modularity because the optimization tends to be trapped by a local maximum especially for large-scale networks. Alternatively we propose a top-down algorithm with implementation of an annealing method and compare effectiveness of the two algorithms. We also compare the results of the community analysis with images of network structure visualized by molecular dynamics method. The vertices belonging to the same community are spatially located close to each other. The community structure determined by the modularity optimization is well reproduced in the network structure obtained by molecular dynamics.
Journal of Physics Conference Series 01/2010; 221(1).
[Show abstract][Hide abstract] ABSTRACT: An agent-based model for firms' dynamics is developed. The model consists of firm agents with identical characteristic parameters and a bank agent. Dynamics of those agents is described by their balance sheets. Each firm tries to maximize its expected profit with possible risks in market. Infinite growth of a firm directed by the "profit maximization" principle is suppressed by a concept of "going concern". Possibility of bankruptcy of firms is also introduced by incorporating a retardation effect of information on firms' decision. The firms, mutually interacting through the monopolistic bank, become heterogeneous in the course of temporal evolution. Statistical properties of firms' dynamics obtained by simulations based on the model are discussed in light of observations in the real economy.
Progress of Theoretical Physics Supplement 02/2009; · 1.25 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: The distribution of labour productivity is investigated by analyzing the longitudinal micro-level data set which contains the detailed financial conditions of large numbers of Japanese companies over the period 1996 -2006. The authors show that the distribution of labour productivity in both the high and low productivity ranges follows a power law distribution. The generalized beta function of the second kind, which asymptotically reproduces a power law function, is applied to explain the distribution of labour productivity. By comparing the power law exponents that characterize high and low productivity ranges, the authors show that for manufacturing industries, inequality in the low productivity range is larger than that in the high productivity range. For the manufacturing industries, the authors also clarify that the change of inequality in the low productivity range has strong correlation with GDP. In addition, by comparing the power law exponents of the high productivity range in the manufacturing and non-manufacturing industries, the authors show that the inequality of the non-manufacturing industry is higher than that of the manufacturing industry.
[Show abstract][Hide abstract] ABSTRACT: We shed light on industrial structure of the economic system in Japan by combining visualization technique and community analysis.
The production network consisting of submillion nodes (firms) and three million links (transactions) is visualized taking
advantage of MD simulation technique. Also communities inherent in such a large-scale network is extracted through maximization
of the modularity using both greedy (bottom-up) and bisection (top-down) algorithms; the bisection method works better. It
is shown that nodes belonging to the same community are located close to each other in a visualization (three-dimensional)
[Show abstract][Hide abstract] ABSTRACT: The thesis proposes to assess the risk topic in the context of foreign investment decisions. In identifying two main risk-related concepts, I have split risks in two categories using a unique criterion: the ratio between the endogenous and exogenous content of the problem. According to it, I have built a pool of risks that the company may have entirely or partially under control (forming the endogenous part of the problem), and a pool with exogenous risks that the company cannot control at all, but can assess and build strategies for their management (forming the exogenous part of the problem). In each category I have identified one source of risk, representing the most important of all risks belonging to the same pool. For the endogenous risks part, credit risk (in its extensive version counterparty risk) was selected. Related to this, there have been additionally discussed the topics of systemic risk and of the risk associated to the impact of the activity of the international rating agencies on the firm financing problem when a company proceeded to debt issuance. The other half of the problem involves the risk of the sector the company activates in. I have found that the risk assessment in this category became an econometric problem of volatility forecasting for a portfolio of a number of selected returns. The discussion complicates given the following factors: 1. The scientific world has not reached yet to a consensus on the superiority of a certain model or group of models that measures volatility. As such, forecasted volatility estimates may depend on the model or methodologies to be used, type of data frequency (high or low), selection of the error statistics etc. As such, decision making as regards the opportunity of the investment becomes highly dependent on econometric choices to be made. 2. Multivariate models are computationally intensive due to the parameter estimation problem. If a large number of stocks are included in the portfolio, the number of est