scholarly journals Dynamic Properties of Foreign Exchange Complex Network

Mathematics ◽  
2019 ◽  
Vol 7 (9) ◽  
pp. 832 ◽  
Author(s):  
Xin Yang ◽  
Shigang Wen ◽  
Zhifeng Liu ◽  
Cai Li ◽  
Chuangxia Huang
Keyword(s):  
Complex Network ◽  
Foreign Exchange ◽  
Minimum Spanning Tree ◽  
Dynamic Properties ◽  
Centrality Measures ◽  
Node Degree ◽  
Survival Ratio ◽  
Network Method ◽  
Tree Length ◽  
Fx Market

The foreign exchange (FX) market, one of the important components of the financial market, is a typical complex system. In this paper, by resorting to the complex network method, we use the daily closing prices of 41 FX markets to build the dynamical networks and their minimum spanning tree (MST) maps by virtue of a moving window correlation coefficient. The properties of FX networks are characterized by the normalized tree length, node degree distributions, centrality measures and edge survival ratios. Empirical results show that: (i) the normalized tree length plays a role in identifying crises and is negatively correlated with the market return and volatility; (ii) 83% of FX networks follow power-law node degree distribution, which means that the FX market is a typical heterogeneous market, and a few hub nodes play key roles in the market; (iii) the highest centrality measures reveal that the USD, EUR and CNY are the three most powerful currencies in FX markets; and (iv) the edge survival ratio analysis implies that the FX structure is relatively stable.

scholarly journals Dynamics of Foreign Exchange Networks: A Time-Varying Copula Approach

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Gang-Jin Wang ◽  
Chi Xie ◽  
Peng Zhang ◽  
Feng Han ◽  
Shou Chen
Keyword(s):  
Foreign Exchange ◽  
Minimum Spanning Tree ◽  
Correlation Coefficients ◽  
Great Majority ◽  
Long Term Memory ◽  
Time Varying ◽  
Long Range Correlations ◽  
Scale Free ◽  
Copula Approach ◽  
Fx Market

Based on a time-varying copula approach and the minimum spanning tree (MST) method, we propose a time-varying correlation network-based approach to investigate dynamics of foreign exchange (FX) networks. In piratical terms, we choose the daily FX rates of 42 major currencies in the international FX market during the period of 2005–2012 as the empirical data. The empirical results show that (i) the distributions of cross-correlation coefficients (distances) in the international FX market (network) are fat-tailed and negatively skewed; (ii) financial crises during the analyzed period have a great effect on the FX network’s topology structure and lead to the US dollar becoming more centered in the MST; (iii) the topological measures of the FX network show a large fluctuation and display long-range correlations; (iv) the FX network has a long-term memory effect and presents a scale-free behavior in the most of time; and (v) a great majority of links between currencies in the international FX market survive from one time to the next, and multistep survive rates of FX networks drop sharply as the time increases.

scholarly journals The Impact of COVID-19 on the Dynamic Topology and Network Flow of World Stock Markets

2021 ◽  
Vol 7 (4) ◽  
pp. 241
Author(s):  
Bilal Ahmed Memon ◽  
Hongxing Yao
Keyword(s):  
Stock Market ◽  
Stock Markets ◽  
Network Flow ◽  
Financial Stability ◽  
Minimum Spanning Tree ◽  
Centrality Measures ◽  
Topological Evolution ◽  
The World ◽  
Tree Length ◽  
The Impact

Studies examining the impact of COVID-19 using network dynamics are scant and tend to evaluate a specific local stock market. We present a thorough investigation of 58 world stock market networks using a complex network approach spanning across the uncertain times that have resulted from the coronavirus outbreak. First, we use the daily closing prices of the world stock market indices to construct dynamic complex networks and sixteen minimum spanning tree (MST) maps for the period from December 2019 to March 2021. Second, we present the topological evolution properties of time-varying MSTs by applying normalized tree length, diameter, average path length, and centrality measures. Moreover, the empirical results suggest that (1) the highest correlation among the world stock markets is observed during the first wave of the COVID-19 pandemic in the months of February–March 2020; (2) most of the MSTs appear lower in hierarchy, and many chain-like structures are formed due to the sheer impact of pandemic-related crises; (3) Germany remained a hub node in many of the MSTs; and (4) the tree severely contracted during the first wave of the COVID-19 outbreak (during the months of February and March 2020) and expanded slightly afterwards. Moreover, the results obtained from this study can be used for the development of financial stability policies and stock market regulations worldwide.

Link prediction based on contribution of neighbors

2020 ◽  
Vol 31 (11) ◽  
pp. 2050158
Author(s):  
Xiang-Chun Liu ◽  
Dian-Qing Meng ◽  
Xu-Zhen Zhu ◽  
Yang Tian
Keyword(s):  
Complex Network ◽  
Link Prediction ◽  
Node Degree ◽  
Prediction Methods ◽  
Obvious Advantage ◽  
Node Similarity ◽  
The Difference

Link prediction based on node similarity has become one of the most effective prediction methods for complex network. When calculating the similarity between two unconnected endpoints in link prediction, most scholars evaluate the influence of endpoint based on the node degree. However, this method ignores the difference in contribution of neighbor (NC) nodes for endpoint. Through abundant investigations and analyses, the paper quantifies the NC nodes to endpoint, and conceives NC Index to evaluate the endpoint influence accurately. Extensive experiments on 12 real datasets indicate that our proposed algorithm can increase the accuracy of link prediction significantly and show an obvious advantage over traditional algorithms.

Survivable Virtual Optical Network Coordinated Mapping with Local Backup

2018 ◽  
Vol 0 (0) ◽  
Author(s):  
Danping Ren ◽  
Wei Wang ◽  
Jinhua Hu ◽  
Jijun Zhao
Keyword(s):  
Spanning Tree ◽  
Minimum Spanning Tree ◽  
Blocking Probability ◽  
Optical Network ◽  
Mapping Method ◽  
Resource Consumption ◽  
Node Degree ◽  
Network Resource ◽  
Mapping Algorithm ◽  
Degree Constraint

AbstractSurvivable virtual optical network (VON) mapping is researched to overcome the ossification of current network architectures. In this paper, we study the survivable VON mapping problem in elastic optical network (EON) with the objective of minimizing the average resource consumption of VON request. We propose a protective algorithm, namely, coordinated mapping algorithm based on minimum spanning tree (CMST), to provide the dedicated protection against the single physical link failure. In CMST, for virtual node mapping, we not only consider the resources constraint but also the node degree constraint. For virtual link mapping, we adopt the coordinated mapping method for part of the virtual nodes and virtual links. And we provide the backup path for the minimum spanning tree link of virtual topology to reduce the resource consumption. Simulation results showed that CMST can reduce the VON request blocking probability and average network resource consumption. And it can increase the revenue of physical network.

scholarly journals Network depth: identifying median and contours in complex networks

2019 ◽  
Vol 8 (4) ◽  
Author(s):  
Giulia Bertagnolli ◽  
Claudio Agostinelli ◽  
Manlio De Domenico
Keyword(s):  
Complex Networks ◽  
Complex Network ◽  
Location Parameter ◽  
Natural Generalization ◽  
Data Depth ◽  
Centrality Measures ◽  
Robust Estimator ◽  
Biologically Relevant ◽  
Geometric Space ◽  
Specific Concept

Abstract Centrality descriptors are widely used to rank nodes according to specific concept(s) of importance. Despite the large number of centrality measures available nowadays, it is still poorly understood how to identify the node which can be considered as the ‘centre’ of a complex network. In fact, this problem corresponds to finding the median of a complex network. The median is a non-parametric—or better, distribution-free—and robust estimator of the location parameter of a probability distribution. In this work, we present the statistical and most natural generalization of the concept of median to the realm of complex networks, discussing its advantages for defining the centre of the system and percentiles around that centre. To this aim, we introduce a new statistical data depth and we apply it to networks embedded in a geometric space induced by different metrics. The application of our framework to empirical networks allows us to identify central nodes which are socially or biologically relevant.

scholarly journals A Century of Topological Coevolution of Complex Infrastructure Networks in an Alpine City

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-16 ◽  
Author(s):  
Jonatan Zischg ◽  
Christopher Klinkhamer ◽  
Xianyuan Zhan ◽  
P. Suresh C. Rao ◽  
Robert Sitzenfrei
Keyword(s):  
Complex Network ◽  
Water Distribution ◽  
Small World ◽  
Water Distribution Network ◽  
Node Degree ◽  
High Dispersion ◽  
Data Set ◽  
Dual Representation ◽  
Infrastructure Networks ◽  
Network Analyses

In this paper, we used complex network analysis approaches to investigate topological coevolution over a century for three different urban infrastructure networks. We applied network analyses to a unique time-stamped network data set of an Alpine case study, representing the historical development of the town and its infrastructure over the past 108 years. The analyzed infrastructure includes the water distribution network (WDN), the urban drainage network (UDN), and the road network (RN). We use the dual representation of the network by using the Hierarchical Intersection Continuity Negotiation (HICN) approach, with pipes or roads as nodes and their intersections as edges. The functional topologies of the networks are analyzed based on the dual graphs, providing insights beyond a conventional graph (primal mapping) analysis. We observe that the RN, WDN, and UDN all exhibit heavy tailed node degree distributions [P(k)] with high dispersion around the mean. In 50 percent of the investigated networks, P(k) can be approximated with truncated [Pareto] power-law functions, as they are known for scale-free networks. Structural differences between the three evolving network types resulting from different functionalities and system states are reflected in the P(k) and other complex network metrics. Small-world tendencies are identified by comparing the networks with their random and regular lattice network equivalents. Furthermore, we show the remapping of the dual network characteristics to the spatial map and the identification of criticalities among different network types through co-location analysis and discuss possibilities for further applications.

scholarly journals A Complex Network Method in Criticality Evaluation of Air Quality Standards

2019 ◽  
Vol 11 (14) ◽  
pp. 3920 ◽  
Author(s):  
Yongchang Wei ◽  
Lei Chen ◽  
Yu Qi ◽  
Can Wang ◽  
Fei Li ◽  
...  
Keyword(s):  
Air Quality ◽  
Complex Network ◽  
Technological Development ◽  
Citation Network ◽  
Quality Standards ◽  
Quality Standard ◽  
Entropy Weight ◽  
Air Quality Standards ◽  
Structural Problems ◽  
Network Method

In recent years, poor air quality has brought serious threats to public health and sustainable development. The air quality standard is an effective prerequisite to ensure the quality of the air. The citation relationships between air quality standards at a certain time point, which reflect technological development and knowledge transition, form a complex network. In this study, an integrated multi-criteria decision making method is proposed to measure the criticality of standards based on a dynamic citation network model. In particular, the Entropy Weight (EW) method is used to set the weights of each node measurement to avoid subjectiveness, while the TOPSIS method is employed to measure the criticality for each air quality standard. A case study based on the data of 444 of China’s national air quality standards reveals that the complex network method facilitates the identification of critical standards effectively. In addition, we found that there exist some structural problems in China’s air quality standard system: the connectivity between standards is insufficient; critical standards are lacking; and the critical standards change over time following the issue of national policies. Finally, policy suggestions are recommended on strengthening inter-standard citation, attaching importance to the revision of critical standards, and the dynamics of critical standards.

scholarly journals Classification of Literary Works: Fractality and Complexity of the Narrative, Essay, and Research Article

Entropy ◽  
2020 ◽  
Vol 22 (8) ◽  
pp. 904
Author(s):  
Aldo Ramirez-Arellano
Keyword(s):  
Complex Network ◽  
Path Length ◽  
Research Topic ◽  
Clustering Coefficient ◽  
Node Degree ◽  
Original Text ◽  
Literary Works ◽  
Research Article ◽  
A Current

A complex network as an abstraction of a language system has attracted much attention during the last decade. Linguistic typological research using quantitative measures is a current research topic based on the complex network approach. This research aims at showing the node degree, betweenness, shortest path length, clustering coefficient, and nearest neighbourhoods’ degree, as well as more complex measures such as: the fractal dimension, the complexity of a given network, the Area Under Box-covering, and the Area Under the Robustness Curve. The literary works of Mexican writers were classify according to their genre. Precisely 87% of the full word co-occurrence networks were classified as a fractal. Also, empirical evidence is presented that supports the conjecture that lemmatisation of the original text is a renormalisation process of the networks that preserve their fractal property and reveal stylistic attributes by genre.

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