scholarly journals Portfolio Correlations in the Bank-Firm Credit Market of Japan

2021 ◽  
Author(s):  
Duc Thi Luu
Keyword(s):  
Matrix Theory ◽  
Global Financial Crisis ◽  
Common Factor ◽  
Principal Component ◽  
Credit Market ◽  
Loan Portfolios ◽  
Cross Correlations ◽  
The Cross ◽  
Random Patterns ◽  
Credit Network

AbstractThe recent global financial crisis has shown portfolio correlations between agents as one of the major channels of risk contagion and amplification. In this work, we analyse the structure and dynamics of the cross-correlation matrix of banks’ loan portfolios in the yearly bank-firm credit network of Japan during the period from 1980 to 2012. Using the methods of Random Matrix Theory (RMT), Principal Component Analysis and complex networks, we aim to detect non-random patterns in the empirical cross-correlations as well as to identify different states of such correlations over time. Our findings suggest that although a majority of portfolio correlations between banks in lending relations to firms are contributed by noise, the top largest eigenvalues always deviate from the random bulk explained by RMT, indicating the presence of non-random patterns governing the correlation dynamics. In particular, we show that this dynamics is mainly driven by a global common factor and a couple of “groups” factors. Furthermore, different states in the credit market can be identified based on the evolution of eigenvalues and associated eigenvectors. For example, during the asset price bubble period in Japan from 1986 to 1991, we find that banks’ loan portfolios tend to be more correlated, showing a significant increase in the level of systemic risk in the credit market. In addition, building Planar Maximally Filtered Graphs from the correlations of different eigenmodes, notably, we observe that the local interaction structure between banks changes in different periods. Typically, when the dominance of a group of banks in one period gradually vanishes, the credit market starts to build-up a different structure in the next period in which another group of banks will become the main actors in the backbone of the cross-correlations.

scholarly journals Forecasting using cross-section average–augmented time series regressions

2020 ◽  
Author(s):  
Hande Karabiyik ◽  
Joakim Westerlund
Keyword(s):  
Time Series ◽  
Cross Section ◽  
Regression Models ◽  
Common Factor ◽  
Principal Component ◽  
Small Sample ◽  
Interactive Effects ◽  
Cross Sectional ◽  
Second Development ◽  
The Cross

Summary There is a large and growing body of literature concerned with forecasting time series variables by the use of factor-augmented regression models. The workhorse of this literature is a two-step approach in which the factors are first estimated by applying the principal components method to a large panel of variables, and the forecast regression is then estimated, conditional on the first-step factor estimates. Another stream of research that has attracted much attention is concerned with the use of cross-section averages as common factor estimates in interactive effects panel regression models. The main justification for this second development is the simplicity and good performance of the cross-section averages when compared with estimated principal component factors. In view of this, it is quite surprising that no one has yet considered the use of cross-section averages for forecasting. Indeed, given the purpose to forecast the conditional mean, the use of the cross-sectional average to estimate the factors is only natural. The present paper can be seen as a reaction to this. The purpose is to investigate the asymptotic and small-sample properties of forecasts based on cross-section average–augmented regressions. In contrast to most existing studies, the investigation is carried out while allowing the number of factors to be unknown.

ON THE APPLICATION OF THE CROSS-CORRELATIONS IN THE CHINESE FUND MARKET: DESCRIPTIVE PROPERTIES AND SCALING BEHAVIORS

2011 ◽  
Vol 14 (01) ◽  
pp. 97-109
Author(s):  
WEIBING DENG ◽  
WEI LI ◽  
XU CAI ◽  
QIUPING A. WANG
Keyword(s):  
Correlation Matrix ◽  
Cross Correlation ◽  
Matrix Theory ◽  
Factorial Moment ◽  
Correlation Coefficients ◽  
Mean Value ◽  
Distribution Of Eigenvalues ◽  
Cross Correlations ◽  
The Cross ◽  
Simple Definition

On the basis of the relative daily logarithmic returns of 88 different funds in the Chinese fund market (CFM) from June 2005 to October 2009, we construct the cross-correlation matrix of the CFM. It is shown that the logarithmic returns follow an exponential distribution, which is commonly shared by some emerging markets. We hereby analyze the statistical properties of the cross-correlation coefficients in different time periods, such as the distribution, the mean value, the standard deviation, the skewness and the kurtosis. By using the method of the scaled factorial moment, we observe the intermittence phenomenon in the distribution of the cross-correlation coefficients. Also by employing the random matrix theory (RMT), we find a few isolated large eigenvalues of the cross-correlation matrix, and the distribution of eigenvalues exhibits the power-law tails. Furthermore, we study the features of the correlation strength with a simple definition.

Book Reviews

2014 ◽  
Vol 52 (3) ◽  
pp. 855-858 ◽  
Keyword(s):  
Nuclear Physics ◽  
Matrix Theory ◽  
Agent Based Modeling ◽  
Urn Model ◽  
Economic Networks ◽  
Random Field Ising Model ◽  
Agent Based ◽  
Cross Correlations ◽  
Credit Network

Sixteen papers, based on the conference on “Econophysics of Agent-Based Models” held at the Saha Institute of Nuclear Physics in November 2012, explore agent-based modeling in the field of econophysics from the perspectives of physicists, economists, mathematicians, and financial engineers. Papers discuss agent-based modeling of zapping behavior of viewers, television commercial allocation, and advertisement markets; agent-based modeling of the housing asset bubble—a simple utility function-based investigation; Urn model-based adaptive multi-arm clinical trials—a stochastic approximation approach; logistic modeling of a religious sect cult and financial features; characterizing financial crisis by means of the three states random field Ising model; themes and applications of kinetic exchange models—redux; the kinetic exchange opinion model—solution in the single parameter map limit; an overview of the new frontiers of economic complexity; Jan Tinbergen's legacy for economic networks—from the gravity model to quantum statistics; a macroscopic order of consumer demand due to heterogeneous consumer behavior on Japanese household demand tested by the random matrix theory; uncovering the network structure of the world currency market—cross-correlations in the fluctuations of daily exchange rates; systemic risk in the Japanese credit network; pricing of goods with bandwagon properties—the curse of coordination; evolution of econophysics; econophysics and sociophysics—problems and prospects; and a discussion on econophysics. Abergel and Chakraborti are with the Laboratory of Mathematics Applied to Systems at the École Centrale Paris. Aoyama is with the Department of Physics at Kyoto University. Chakrabarti is at the Saha Institute of Nuclear Physics. Ghosh is with the Theoretical Condensed Matter Physics Division at the Saha Institute of Nuclear Physics.

scholarly journals Convergence in the UK direct real estate market

2017 ◽  
Vol 35 (4) ◽  
pp. 382-396
Author(s):  
Stephen Lee
Keyword(s):  
Real Estate ◽  
Global Financial Crisis ◽  
Common Factor ◽  
Principal Component ◽  
Spillover Effects ◽  
Real Estate Market ◽  
Sample Period ◽  
Market Segments ◽  
Content Type ◽  
The Uk

Purpose The purpose of this paper is to empirically examine the issue of convergence in the monthly returns, rental growth and yields for ten market segments in the UK direct real estate market, using monthly data over the period from January 1987 to December 2014. Design/methodology/approach The methodology used to determine convergence is principal component analysis as it provides an assessment of the extent to which the variance of the market segments can be represented by a single common factor, explaining their long-run behaviour, and the degree of independence between the market segments. Findings The results suggest that there is strong evidence of convergence over the entire sample period in relation to monthly returns and yields but less evidence of convergence in rental growth, which confirms the findings in previous studies in international markets. Practical implications The evidence also suggests that convergence has increased over the sample period and that convergence is period specific and was particularly strong during and after the period of the Global Financial Crisis, which implies that the UK direct real estate market is largely integrated and as a consequence the extent of diversification potential in the market is still severely limited. Social implications The convergence in returns has crucial implications for investors as it leaves investors exposed to the same structural shocks and so magnifies the importance of volatility spillover effects, limits their ability to create well-diversified portfolios and make it more difficult for fund managers to outperform the market. Originality/value This is the first paper to examine the convergence in the UK direct real estate market.

Comparison of Principal Component Solutions in Two Populations

Methodology ◽  
2016 ◽  
Vol 12 (1) ◽  
pp. 11-20 ◽  
Author(s):  
Gregor Sočan
Keyword(s):  
Simulation Study ◽  
Principal Components ◽  
Common Factor ◽  
Principal Component ◽  
Component Model ◽  
Bootstrap Procedure ◽  
Factor Loadings ◽  
Component Loadings ◽  
Principal Component Model ◽  
Two Populations

Abstract. When principal component solutions are compared across two groups, a question arises whether the extracted components have the same interpretation in both populations. The problem can be approached by testing null hypotheses stating that the congruence coefficients between pairs of vectors of component loadings are equal to 1. Chan, Leung, Chan, Ho, and Yung (1999) proposed a bootstrap procedure for testing the hypothesis of perfect congruence between vectors of common factor loadings. We demonstrate that the procedure by Chan et al. is both theoretically and empirically inadequate for the application on principal components. We propose a modification of their procedure, which constructs the resampling space according to the characteristics of the principal component model. The results of a simulation study show satisfactory empirical properties of the modified procedure.

The Lived Experience of Financialization at the UK Financial Fringe

2021 ◽  
pp. 1-22
Author(s):  
LINDSEY APPLEYARD ◽  
CARL PACKMAN ◽  
JORDON LAZELL ◽  
HUSSAN ASLAM
Keyword(s):  
Lived Experience ◽  
Financial Services ◽  
Global Financial Crisis ◽  
Credit Market ◽  
Short Term ◽  
Dramatic Decline ◽  
The Everyday ◽  
The Subject ◽  
The Uk ◽  
The Impact

Abstract The financialization of everyday life has received considerable attention since the 2008 global financial crisis. Financialization is thought to have created active financial subjects through the ability to participate in mainstream financial services. While the lived experience of these mainstream financial subjects has been the subject of close scrutiny, the experiences of financial subjects at the financial fringe have been rarely considered. In the UK, for example, the introduction of High-Cost, Short-Term Credit [HCSTC] or payday loan regulation was designed to protect vulnerable people from accessing unaffordable credit. Exploring the impact of HCSTC regulation is important due to the dramatic decline of the high-cost credit market which helped meet essential needs in an era of austerity. As such, the paper examines the impact of the HCSTC regulation on sixty-four financially marginalized individuals in the UK that are unable to access payday loans. First, we identify the range of socioeconomic strategies that individuals employ to manage their finances to create a typology of financial subjectivity at the financial fringe. Second, we demonstrate how the temporal and precarious nature of financial inclusion at the financial fringe adds nuance to existing debates of the everyday lived experience of financialization.

scholarly journals Asymptotic analysis for dispersion relations and travel times in noise cross-correlations: spherically symmetric case

2018 ◽  
Vol 474 (2218) ◽  
pp. 20180382
Author(s):  
Tianshi Liu ◽  
Haiming Zhang
Keyword(s):  
Asymptotic Analysis ◽  
Surface Waves ◽  
Green's Functions ◽  
Green’S Functions ◽  
Dispersion Relations ◽  
Body Waves ◽  
Spherically Symmetric ◽  
Travel Times ◽  
Cross Correlations ◽  
The Cross

The cross-correlations of ambient noise or earthquake codas are massively used in seismic tomography to measure the dispersion curves of surface waves and the travel times of body waves. Such measurements are based on the assumption that these kinematic parameters in the cross-correlations of noise coincide with those in Green's functions. However, the relation between the cross-correlations of noise and Green's functions deserves to be studied more precisely. In this paper, we use the asymptotic analysis to study the dispersion relations of surface waves and the travel times of body waves, and come to the conclusion that for the spherically symmetric Earth model, when the distribution of noise sources is laterally uniform, the dispersion relations of surface waves and the travel times of SH body-wave phases in noise correlations should be exactly the same as those in Green's functions.

scholarly journals Implementing Horn's Parallel Analysis for Principal Component Analysis and Factor Analysis

2009 ◽  
Vol 9 (2) ◽  
pp. 291-298 ◽  
Author(s):  
Alexis Dinno
Keyword(s):  
Principal Component Analysis ◽  
Factor Analysis ◽  
Common Factor ◽  
Principal Component ◽  
Component Analysis ◽  
Parallel Analysis ◽  
Common Factor Analysis

I present paran, an implementation of Horn's parallel analysis criteria for factor or component retention in common factor analysis or principal component analysis in Stata. The command permits classical parallel analysis and more recent extensions to it for the pca and factor commands. paran provides a needed extension to Stata's built-in factor- and component-retention criteria.

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