The Index cohesive effect on stock market correlations

Shapira, Yoash; Kenett, Dror Y.; Ben‐Jacob, Eshel

doi:10.1140/epjb/e2009-00384-y

Cited by 93 publications

(89 citation statements)

References 33 publications

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“…Studying Fig. 2, a bursting behavior for the intra-correlations for each market is observed, as is consistent with previous findings 7,18 . Furthermore, a similarity in the dynamics of intra-correlation bursts is observable.…”

Section: Dynamics Intra-correlationssupporting

confidence: 91%

“…Partial correlation is a useful tool to investigate how the correlation between two stocks depends on the correlation of each of the stocks with a third mediating stock or with the index as is considered here. The residual, or partial, correlation between stocks i and j, using the index (m) as the mediating variable is defined by 7,31,32 .…”

Section: The Correlation Influence and Correlation Dependencymentioning

confidence: 99%

“…A large part of the current literature deals with the analysis of single markets. The variety of different methods is quite large, with many analyses employing Pearson's correlations 4,5,6,7 but also other methodologies have been used, such as comovement measures 8 , recurrence patterns 9 , and regime switching approaches 10,11 .…”

Section: Introductionmentioning

confidence: 99%

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Correlations and Dependencies in the Global Financial Village

Kenett

Raddant

Zatlavi

et al. 2012

Int. J. Mod. Phys. Conf. Ser.

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The high degree of coupling between global financial markets has made the financial village prone to systemic collapses. Here we present a new methodology to assess and quantify inter-market relations. The approach is based on meta-correlations (correlations between the intra-market correlations), and a Dependency Network analysis approach. We investigated the relations between six important world markets -U.S., U.K., Germany, Japan, China and India from January 2000 until December 2010. Our findings show that while the developed Western markets (U.S., U.K., Germany), are highly correlated, the inter-dependencies between these markets and the Eastern markets (India and China) are very volatile and with noticeable maxima at times of global world events. Finally, using the Dependency network approach, we quantify the flow of information between the different markets, and how markets affect each other. We observe that German and U.K. stocks show a large amount of coupling, while other markets are more segmented. These and additional reported findings illustrate that this methodological framework provides a way to quantify interdependencies in the global market and their

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Section: Dynamics Intra-correlationssupporting

confidence: 91%

Section: The Correlation Influence and Correlation Dependencymentioning

confidence: 99%

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Correlations and Dependencies in the Global Financial Village

Kenett

Raddant

Zatlavi

et al. 2012

Int. J. Mod. Phys. Conf. Ser.

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“…The basis of this methodology is to investigate the partial correlations between a given set of variables (or nodes) of the network. Using the concept of partial correlations [118][119][120][121][122][123][124], preliminary results show that it is possible to quantify how one node in the network affects the link between other nodes in the network. This new class of correlation-based networks is able to uncover important hidden information about the system.…”

Section: Dependency Relations In Network and Network Of Networkmentioning

confidence: 99%

Challenges in network science: Applications to infrastructures, climate, social systems and economics

Havlin

Kenett

Ben‐Jacob

et al. 2012

Eur. Phys. J. Spec. Top.

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165

102

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Abstract. Network theory has become one of the most visible theoretical frameworks that can be applied to the description, analysis, understanding, design and repair of multi-level complex systems. Complex networks occur everywhere, in man-made and human social systems, in organic and inorganic matter, from nano to macro scales, and a e-mail: havlins@gmail.com b e-mail: drorkenett@gmail.com c e-mail: eshelbj@gmail.com d e-mail: armin.bunde@physik.uni-giessen.de e e-mail: reuven@macs.biu.ac.il f e-mail: hans@ifb.baug.ethz.ch g e-mail: jan.kantelhardt@physik.uni-halle.de h e-mail: kertesz@phy.bme.hu i e-mail: kirk@cs.huji.ac.il j e-mail: kurths@pik-potsdam.de k e-mail: juval@post.tau.ac.il l e-mail: sorin@vms.huji.ac.il 274The European Physical Journal Special Topics in natural and anthropogenic structures. New applications are developed at an ever-increasing rate and the promise for future growth is high, since increasingly we interact with one another within these vital and complex environments. Despite all the great successes of this field, crucial aspects of multi-level complex systems have been largely ignored. Important challenges of network science are to take into account many of these missing realistic features such as strong coupling between networks (networks are not isolated), the dynamics of networks (networks are not static), interrelationships between structure, dynamics and function of networks, interdependencies in given networks (and other classes of links, including different signs of interactions), and spatial properties (including geographical aspects) of networks. This aim of this paper is to introduce and discuss the challenges that future network science needs to address, and how different disciplines will be accordingly affected.

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“…Total influence was developed by Kenett et al in order to compute and investigate the mutual dependencies between network nodes from the matrices of node-node correlations. The basis of this method is the partial correlations between a given set of variables (or nodes) of the network [5,[21][22][23]. This new approach quantifies how a particular node in a network affects the links between other nodes, and is able to uncover important hidden information about the system.…”

Section: Introductionmentioning

confidence: 99%

Dependency Relations among International Stock Market Indices

Sandoval

Mullokandov

Kenett³

2015

JRFM

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We develop networks of international stock market indices using information and correlation based measures. We use 83 stock market indices of a diversity of countries, as well as their single day lagged values, to probe the correlation and the flow of information from one stock index to another taking into account different operating hours. Additionally, we apply the formalism of partial correlations to build the dependency network of the data, and calculate the partial Transfer Entropy to quantify the indirect influence that indices have on one another. We find that Transfer Entropy is an effective way to quantify the flow of information between indices, and that a high degree of information flow between indices lagged by one day coincides to same day correlation between them.

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The Index cohesive effect on stock market correlations

Cited by 93 publications

References 33 publications

Correlations and Dependencies in the Global Financial Village

Correlations and Dependencies in the Global Financial Village

Challenges in network science: Applications to infrastructures, climate, social systems and economics

Dependency Relations among International Stock Market Indices

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