Network analysis of a financial market based on genuine correlation and threshold method

Namaki, Ali; Shirazi, Amir Hossein Masnadi; Raei, Reza; Jafari, G. R.

doi:10.1016/j.physa.2011.06.033

Cited by 178 publications

(122 citation statements)

References 43 publications

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“…In this section, we describe our specic adaptation of the methodology of Mantegna [1] and Namaki et al [7]. We started by dening the logarithmic returns of 66 assets…”

Section: Methodsmentioning

confidence: 99%

“…In addition to MST, several alternative methodologies can be mentioned. In order to display only the relevant relations between assets Huang et al [5], Tse et al [6], Namaki et al [7] have used the threshold method, where the edge is added only when the correlation between the pair of assets exceeds a given threshold value. The most remarkable dierence between the threshold and MST ltering consists in the formation of graph cycles (present only in the case of the threshold method).…”

Section: Introductionmentioning

confidence: 99%

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Revealing Ownership Structure of Funds Using Minimum Spanning Tree

et al. 2014

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The traditional method of analysing a time series of stocks and funds is to use simple Pearson correlations. However, experience shows that cross-correlations are not an accurate indicator of the mutual ownership relations. We show that the minimum spanning tree methodology, previously used to perform more comprehensive studies of asset returns correlations, can be used to deduce the underlying ownership structure with reasonable accuracy. We also show that adjusting the time series for a common trend of stocks and subsequent ltering of the short term variations of returns using the ARIMA model is a prerequisite for this application of the minimum spanning tree.

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“…In this section, we describe our specic adaptation of the methodology of Mantegna [1] and Namaki et al [7]. We started by dening the logarithmic returns of 66 assets…”

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Revealing Ownership Structure of Funds Using Minimum Spanning Tree

et al. 2014

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show abstract

“…The method of correlation networks has been applied to the structural transition of financial systems during a crisis in a local market [18]. In the Tehran stock market and the DJIA, a scale-free threshold network in a restricted threshold has been observed [19]. Longfeng Zhao et al [20] found some long-duration edges that serve as the backbone of the stock market during crises.…”

Section: Introductionmentioning

confidence: 99%

Construction of Complex Network with Multiple Time Series Relevance

Huang

Wang³

et al. 2018

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Multivariate time series data, which comprise a set of ordered observations for multiple variables, are pervasively generated in weather conditions, traffic, financial stocks, etc. Therefore, it is of great significance to analyze the correlation between multiple time series. Financial stocks generate a significant amount of multivariate time series data that can be used to build networks that reflect market behavior. However, traditional commercial complex networks cannot fully utilize the multiple attributes of stocks and redundant filter relationships and reveal a more authentic financial stock market. We propose a fusion similarity of multiple time series and construct a threshold network with similarity. Furthermore, we define the connectivity efficiency to choose the best threshold, establishing a high connectivity efficiency network with the optimal network threshold. By searching the central node in the threshold network, we have found that the network center nodes constructed by our proposed method have a more comprehensive industry coverage than the traditional techniques to build the systems, and this also proves the superiority of this method.

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“…However, how to convert the complexity of financial markets into a theoretical model of complex networks is still an open issue in the study. Namiki et al [22] built the complex networks using the threshold method. Tabak et al [23] built the minimum spanning tree for researching Brazil stock market and Brazil fund finance.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Chinese Stock Market by Using the Method of Visibility Graph

Liu¹,

Wang²,

Wei³

2017

Open Cyber

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Many researchers studied the complexity of financial markets based on complex networks methods. The conversion of financial markets into complex networks is an open issue. In this paper, the data of 2571 stock companies in 2012 and the data of 2578 stock companies in 2013 are collected from Chinese stock market. Every year, data of these stock companies are randomly arranged. These data are then converted into some complex networks based on the visibility graph method. For these complex networks, degree distribution and clustering coefficient are considered. Our results show that the complex networks have the powerlaw distribution and small-world properties. The Pareto principle is also testified by the rank of average degree of companies in Chinese stock.

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Network analysis of a financial market based on genuine correlation and threshold method

Cited by 178 publications

References 43 publications

Revealing Ownership Structure of Funds Using Minimum Spanning Tree

Revealing Ownership Structure of Funds Using Minimum Spanning Tree

Construction of Complex Network with Multiple Time Series Relevance

Analysis of Chinese Stock Market by Using the Method of Visibility Graph

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