Systemic risk and hierarchical transitions of financial networks

Nobi, Ashadun,Lee, Jae Woo American Institute of Physics 2017 Chaos Vol.27 No.6

Random Matrix Theory and Cross-correlations in Global Financial Indices and Local Stock Market Indices

Ashadun Nobi,맹성은,하경균,이재우 한국물리학회 2013 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.62 No.4

We analyzed cross-correlations between price fluctuations of global financial indices (20 daily stock indices over the world) and local indices (daily indices of 200 companies in the Korean stock market) by using random matrix theory (RMT). We compared eigenvalues and components of the largest and the second largest eigenvectors of the cross-correlation matrix before, during, and after the global financial the crisis in the year 2008. We find that the majority of its eigenvalues fall within the RMT bounds [λ_-,λ₊], where λ_- and λ₊ are the lower and the upper bounds of the eigenvalues of random correlation matrices. The components of the eigenvectors for the largest positive eigenvalues indicate the identical financial market mode dominating the global and local indices. On the other hand, the components of the eigenvector corresponding to the second largest eigenvalue are positive and negative values alternatively. The components before the crisis change sign during the crisis, and those during the crisis change sign after the crisis. The largest inverse participation ratio (IPR) corresponding to the smallest eigenvector is higher after the crisis than during any other periods in the global and local indices. During the global financial the crisis, the correlations among the global indices and among the local stock indices are perturbed significantly. However, the correlations between indices quickly recover the trends before the crisis.

Structural Changes in the Minimal Spanning Tree and the Hierarchical Network in the Korean Stock Market around the Global Financial Crisis

Ashadun Nobi,맹성은,하정균,이재우 한국물리학회 2015 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.66 No.8

This paper considers stock prices in the Korean stock market during the 2008 global financial crisis by focusing on three time periods: before, during, and after the crisis. Complex networks are extracted from cross-correlation coefficients between the normalized logarithmic return of the stock price time series of firms. The minimal spanning trees (MSTs) and the hierarchical network (HN) are generated from cross-correlation coefficients. Before and after the crisis, securities firms are located at the center of the MST. During the crisis, however, the center of the MST changes to a firm in heavy industry and construction. During the crisis, the MST shrinks in comparison to that before and that after the crisis. This topological change in the MST during the crisis reflects a distinct effect of the global financial crisis. The cophenetic correlation coefficient increases during the crisis, indicating an increase in the hierarchical structure during in this period. When crisis hits the market, firms behave synchronously, and their correlations are higher than those during a normal period.

Entropy and scaling behaviors of international trade patterns

Nobi Ashadun,Milu Sharmin Akter,Lee Jae Woo 한국물리학회 2023 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.83 No.9

We investigate the impact of international commodities trade on economic growth of fve Asian countries including China over the last two decades. We examine the exports of eight commodity categories from 1995 to 2018. Firstly, we calculate trade entropy by considering the probability of exporting a product from one country to another. Our analysis reveals a signifcant increase in China’s trade entropy for manufactured goods primarily classifed by material, compared to other products. The strong correlation between changes in gross domestic product (GDP) and trade volume in China indicates a remarkable contribution of manufactured goods to GDP during the studied period. Additionally, we establish a power law-scaling relation between GDP and product exports over time. Notably, the growth of manufactured goods from China exhibits a super-linear relationship with GDP.

Dynamic of consumer groups and response of commodity markets by principal component analysis

Nobi, Ashadun,Alam, Shafiqul,Lee, Jae Woo Elsevier 2017 PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIO Vol.482 No.-

<P><B>Abstract</B></P> <P>This study investigates financial states and group dynamics by applying principal component analysis to the cross-correlation coefficients of the daily returns of commodity futures. The eigenvalues of the cross-correlation matrix in the 6-month timeframe displays similar values during 2010–2011, but decline following 2012. A sharp drop in eigenvalue implies the significant change of the market state. Three commodity sectors, energy, metals and agriculture, are projected into two dimensional spaces consisting of two principal components (PC). We observe that they form three distinct clusters in relation to various sectors. However, commodities with distinct features have intermingled with one another and scattered during severe crises, such as the European sovereign debt crises. We observe the notable change of the position of two dimensional spaces of groups during financial crises. By considering the first principal component (PC1) within the 6-month moving timeframe, we observe that commodities of the same group change states in a similar pattern, and the change of states of one group can be used as a warning for other group.</P> <P><B>Highlights</B></P> <P> <UL> <LI> The principal component analysis applied to the time series of commodity futures. </LI> <LI> The drop of the largest eigenvalue corresponds to the market crash. </LI> <LI> Groups of commodities observed during the financial crisis. </LI> </UL> </P>

Financial States of World Financial and Commodities Markets Around Sovereign Debt Crisis

Ashadun Nobi,이재우 한국물리학회 2017 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.71 No.10

We applied a threshold method to construct a complex network from cross-correlations coefficients of 46 daily time series comprised of 23 global indices and 23 commodity futures from 2010 - 2014. We identify financial states of both global indices and commodity futures based on the change of the network structure. The trend of the average correlation is decreasing except sharp peak during crises during the study period. The threshold networks are generated at a threshold value of = 0.1 and the change of degrees of each node over time is used to identify the financial state for each index. We observe that commodity futures, such as EU CO2 emission, live cattle, natural gas as well as the financial indices of Jakarta and Indonesia stock exchange (JKSE) and Kuala Lumpur stock exchange (KLSE) change states frequently. By the average change in links we identify the indices which are more reactive to crises.

Threshold Network of a Financial Market Using the P-value of Correlation Coefficients

하경균,이재우,Ashadun Nobi 한국물리학회 2015 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.66 No.12

Threshold methods in financial networks are important tools for obtaining important information about the financial state of a market. Previously, absolute thresholds of correlation coefficients have been used; however, they have no relation to the length of time. We assign a threshold value depending on the size of the time window by using the P-value concept of statistics. We construct a threshold network (TN) at the same threshold value for two different time window sizes in the Korean Composite Stock Price Index (KOSPI). We measure network properties, such as the edge density, clustering coefficient, assortativity coefficient, and modularity. We determine that a significant difference exists between the network properties of the two time windows at the same threshold, especially during crises. This implies that the market information depends on the length of the time window when constructing the TN. We apply the same technique to Standard and Poor’s 500 (S&P500) and observe similar results.

State and Network Structures of Stock Markets Around the Global Financial Crisis

Lee, Jae Woo,Nobi, Ashadun Springer-Verlag 2018 Computational economics Vol.51 No.2

<P>We consider the effects of the 2008 global financial crisis on the global stock market before, during, and after the crisis. We generate complex networks from a cross-correlation matrix such as the threshold network (TN) and the minimal spanning tree (MST). In the threshold network, we assign a threshold value by using the mean and standard deviation of cross-correlation coefficients. When the threshold is equal to the mean of these coefficients, we observe a giant cluster composed of three economic zones in all three periods. We find that during the crisis, the countries in the Asian zone were weakly connected and those in the American zone were tightly linked to the countries in the European zone. At a large threshold, the three economic zones were fragmented. The European countries connected tightly, but the Asian countries bound weakly. The MST constructed from the distance matrix. In the MST, France remained a hub node in all three periods. The size of the MST shrank slightly during the crisis. We observe a scaling relation between the network distance of nodes from the central hub (France) and the geometrical distance. We observe the topological change of the financial network structure during the global financial crisis. The TN and MST are complementary roles to understand the connecting structure of financial complex networks. The TN reveals to observe the clustering effects and robustness of the cluster during the financial crisis. The MST shows the central hub and connecting node among the economic zones.</P>

Changes of Hierarchical Network in Local and World Stock Market

Enayet Ullah Patwary,이종열,Ashadun Nobi,김두환,이재우 한국물리학회 2017 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.71 No.7

We consider the cross-correlation coefficients of the daily returns in the local and global stock markets. We generate the minimal spanning tree (MST) using the correlation matrix. We observe that the MSTs change their structure from chain-like networks to star-like networks during periods of market uncertainty. We quantify the measure of the hierarchical network utilizing the value of the hierarchy measured by the hierarchical path. The hierarchy and betweenness centrality characterize the state of the market regarding the impact of crises. During crises, the non-financial company is established as the central node of the MST. However, before the crisis and during stable periods, the financial company is occupying the central node of the MST in the Korean and the U.S. stock markets. The changes in the network structure and the central node are good indicators of an upcoming crisis.