Comparing the structure of an emerging market with a mature one under global perturbation

Namaki, Ali; Jafari, G. R.; Raei, Reza

doi:10.1016/j.physa.2011.04.004

Cited by 23 publications

(16 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…From random matrix theory, we know that the eigenvalues-in the real matrix-which deviate from the range of the eigenvalues-in the random matrix-possess relatively more complete information from the system [51,58,59]. It can be shown that the majority of the eigenvalues of coupling matrices, agree with the random matrix predictions, but the largest eigenvalue has deviations from those estimations [50,57,58,73].…”

Section: Methodsmentioning

confidence: 91%

See 1 more Smart Citation

Analysis of the Global Banking Network by Random Matrix Theory

et al. 2021

View full text Add to dashboard Cite

Since the financial crisis of 2008, the network analysis of financial systems has attracted a lot of attention. In this paper, we analyze the global banking network via the method of Random Matrix Theory. By applying that method on a cross border lending network, it is shown that while the connectivity between different parts of the network has risen and the profile of transactions has diversified, the role of hubs remains important in the weighted perspective. The largest eigenvalue of the transaction matrix as the leading mode of the system shows sharp growth since 2002. As well, it is observed that its growth has diminished since 2008. This indicates that the crisis of 2008 has left a long-lasting footprint on the financial system. Analyzing the mean value of the participation ratio reveals the fact that the role of countries in forming small modes, has increased since 2002. In our final analysis, we provide snapshots of the hubs in the network over time. We observe that the share of countries in total transactions is not equal to their share in shaping the eigenvector of the largest eigenvalue. In 2018 for example, while the United Kingdom leads the share of transactions, it is the United States that has the largest value in the leading eigenvector. The proposed technique in the paper can be useful for analyzing different types of interaction networks between countries.

show abstract

Section: Methodsmentioning

confidence: 91%

“…Random Matrix Theory is one of the useful methods for analyzing the behavior of complex systems [16,[43][44][45][46][47][48][49][50][51][52][53][54].…”

Section: Introductionmentioning

confidence: 99%

Analysis of the Global Banking Network by Random Matrix Theory

et al. 2021

View full text Add to dashboard Cite

show abstract

“…These deviating eigenvalues contains useful information about the collective behavior. To be more precise, it was shown that large eigenvalues show the markets' trend and the largest eigenvalue indicates the largest collective mode in markets, see e.g., 8,9,11,15 . In the following, we study collective behavior in an abstract market named "world stock market" by taking a different path using the proposed method of this paper.…”

Section: Forty Markets As a World Stock Marketmentioning

confidence: 99%

Emergence of world-stock-market network

Saeedian

Jamali

Kamali

et al. 2019

Physica A: Statistical Mechanics and its Applications

Self Cite

View full text Add to dashboard Cite

In the age of globalization, it is natural that the stock market of each country is not independent form the other markets. In this case, collective behavior could be emerged form their dependency together. This article studies the collective behavior of a set of forty influential markets in the world economy with the aim of exploring a global financial structure that could be called world-stock-market network. Towards this end, we analyze the cross-correlation matrix of the indices of these forty markets using Random Matrix Theory (RMT). We find the degree of collective behavior among the markets and the share of each market in their structural formation. This finding together with the results obtained from the same calculation on four stock markets reinforce the idea of a world financial market. Finally, we draw the dendrogram of the cross-correlation matrix to make communities in this abstract global market visible. The dendrogram, drawn by at least thirty percent of correlation, shows that the world financial market comprises three communities each of which includes stock markets with geographical proximity.

show abstract

“…In the study of lim et al [24], these events were applied to the correlation matrix in both local and global perturbations. They emphasized that markets are more sensitive to global perturbation and in another study [25]they expressed mature markets are more sensitive to global perturbation than emerging markets.…”

Section: Introductionmentioning

confidence: 99%

Comparing the collective behavior of banking industry

Vahabi,

Namaki,

Raei

2020

Preprint

View full text Add to dashboard Cite

One of the most important features of capital markets as an adaptive complex networks is their collective behavior. In this paper, we have analyzed the banking sectors of 4 world stock markets,which composed of emerging and matures ones. By applying one the important complexity notions, Random matrix theory(RMT), it is founded that mature markets have a higher degree of collective behavior,Even though we used RMT tools: participation ratio(PR), node participation ratio(NPR)and relative participation ratio(RPR) , which NPR illustrated independent banks than whole market and RPR compared collective behavior of markets by a normal range. By applying local and global perturbations, we concluded that mature markets are more vulnerable to perturbations due to the high level of collective behavior. Finally, by drawing the dendrograms and heat maps of the correlation matrices,we reaffirmed the stronger cross-correlation in the mature markets.

show abstract

Comparing the structure of an emerging market with a mature one under global perturbation

Cited by 23 publications

References 33 publications

Analysis of the Global Banking Network by Random Matrix Theory

Analysis of the Global Banking Network by Random Matrix Theory

Emergence of world-stock-market network

Comparing the collective behavior of banking industry

Contact Info

Product

Resources

About