Minimal spanning tree problem in stock networks analysis: An efficient algorithm

Djauhari, Maman A.; Gan, Siew Lee

doi:10.1016/j.physa.2012.12.032

Cited by 17 publications

(13 citation statements)

References 16 publications

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“…It provides N-1 stronger (i.e., shorter) links between stocks that span all the stocks. In this paper the improved Kruskal's algorithm suggested by Djauhari and Gan [53] is used. Fig.…”

Section: Resultsmentioning

confidence: 99%

Correlation network analysis for multi-dimensional data in stocks market

Kazemilari

Djauhari

2015

Physica A: Statistical Mechanics and its Applications

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“…It provides N-1 stronger (i.e., shorter) links between stocks that span all the stocks. In this paper the improved Kruskal's algorithm suggested by Djauhari and Gan [53] is used. Fig.…”

Section: Resultsmentioning

confidence: 99%

Correlation network analysis for multi-dimensional data in stocks market

Kazemilari

Djauhari

2015

Physica A: Statistical Mechanics and its Applications

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“…we construct the MST for N currencies in the FX market via using the Kruskal's algorithm [58,59]. For each time scale s, the MST network of the FX market connects the N currencies (nodes) with N−1 stronger links such that no loops are produced, i.e., the FX network is structured with the strongest cross-correlations of each currency [23].…”

Section: Methodsmentioning

confidence: 99%

Statistical Properties of the Foreign Exchange Network at Different Time Scales: Evidence from Detrended Cross-Correlation Coefficient and Minimum Spanning Tree

Wang

Xie

Chen

et al. 2013

Entropy

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Abstract:We investigate the statistical properties of the foreign exchange (FX) network at different time scales by two approaches, namely the methods of detrended cross-correlation coefficient (DCCA coefficient) and minimum spanning tree (MST). The daily FX rates of 44 major currencies in the period of 2007-2012 are chosen as the empirical data. Based on the analysis of statistical properties of cross-correlation coefficients, we find that the cross-correlation coefficients of the FX market are fat-tailed. By examining three MSTs at three special time scales (i.e., the minimum, medium, and maximum scales), we come to some conclusions: USD and EUR are confirmed as the predominant world currencies; the Middle East cluster is very stable while the Asian cluster and the Latin America cluster are not stable in the MSTs; the Commonwealth cluster is also found in the MSTs. By studying four evaluation criteria, we find that the MSTs of the FX market present diverse topological and statistical properties at different time scales. The scale-free behavior is observed in the FX network at most of time scales. We also find that most of links in the FX network survive from one time scale to the next.

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“…This is one of the advantages of Kruskal's algorithm that is usually used in stocks network analysis based on MST such as presented in the literature, for example, Refs. [3,4,7,12,13,21,30,34,40]. Based on that property, the merits of the proposed method can be seen in Section 4 where the promising results are presented and discussed.…”

Section: Motivation: Case Of Nysementioning

confidence: 97%

“…If C consists of more than one MST, an optimal one is still hard to find even in F . Here, we develop the idea of Djauhari and Gan [40] to simplify the problem and get the solution.…”

Section: Construction Of the Forestmentioning

confidence: 99%