scholarly journals A Network Analysis of Shariah-Compliant Stocks across Global Financial Crisis: A Case of Malaysia

2019 ◽  
Vol 13 (7) ◽  
pp. 80 ◽  
Author(s):  
Fatin Nur Amirah Mahamood ◽  
Hafizah Bahaludin ◽  
Mimi Hafizah Abdullah
Keyword(s):  
Topological Structure ◽  
Spanning Tree ◽  
Minimum Spanning Tree ◽  
Global Financial Crisis ◽  
Closeness Centrality ◽  
Centrality Measures ◽  
Financial Networks ◽  
Eigenvector Centrality ◽  
Land Holdings ◽  
Year 2000

Financial network is a complex system in which transaction of securities take place. Due to its complexity, a minimum spanning tree (MST) technique is used to visualize the structure. This paper investigates the topological structure of 125 shariah-compliant stocks traded in Bursa Malaysia from the year 2000 until 2017. Financial networks of the shariah-compliant stocks are constructed using MST for three duration periods namely the pre-crisis, during crisis and post-crisis. To determine the important stocks in the networks, centrality measures are applied such as degree centrality, betweenness centrality, closeness centrality and eigenvector centrality. Lastly, overall centrality measures are computed to identify the overall characteristic of each node. The findings showed that, KUB Malaysia Berhad was the most influential stock in the pre-crisis and crisis periods. While, MK Land Holdings was the main stock in the post-crisis network.

scholarly journals Stock Networks Analysis in Kuala Lumpur Stock Exchange

2014 ◽  
Vol 8 (2) ◽  
Author(s):  
Gan Siew Lee ◽  
Maman Abdurachman Djauhari
Keyword(s):  
Minimum Spanning Tree ◽  
Stock Exchange ◽  
Closeness Centrality ◽  
Correlation Structure ◽  
Centrality Measures ◽  
Kuala Lumpur ◽  
Eigenvector Centrality ◽  
Economic Information ◽  
Topological Network ◽  
Networks Analysis

This paper deals with an analysis of correlation structure among stocks traded in Kuala Lumpur Stock Exchange (KLSE) by using network analysis approach. The minimum spanning tree (MST) related to that correlation structure will be presented to have a better understanding about stocks topological network. An overall centrality measure will be introduced to filter the economic information contained in the MST. This measure will give additional economic information that cannot be delivered by the conventional centrality measures such as degree centrality, betweenness centrality, closeness centrality and eigenvector centrality.

scholarly journals A COMPARISON OF CENTRALITY MEASURES IN SUSTAINABLE DEVELOPMENT GOALS

2020 ◽  
Vol 14 (3) ◽  
pp. 309-320
Author(s):  
Sena Ariesandy ◽  
Ema Carnia ◽  
Herlina Napitupulu
Keyword(s):  
Sustainable Development ◽  
Millennium Development Goals ◽  
Sustainable Development Goals ◽  
Closeness Centrality ◽  
Centrality Measures ◽  
Degree Centrality ◽  
Eigenvector Centrality ◽  
Global Problems ◽  
Calculation Results ◽  
Development Goals

The Millennium Development Goals (MDGs), which began in 2000 with 8 goal points, have not been able to solve the global problems. The MDGs were developed into Sustainable Development Goals (SDGs) in 2015 with 17 targeted goal points achieved in 2030. Until now, methods for determining the priority of SDGs are still attractive to researchers. Centrality is one of the tools in determining the priority goal points on a network by using graph theory. There are four measurements of centrality used in this paper, namely degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality. The calculation results obtained from the four measurements are compared, analyzed, to conclud which goal points are the most prior and the least prior. From the results obtained the most priority goal points in Sustainable Development Goals.

scholarly journals The Volatility Forecasting Power of Financial Network Analysis

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-17 ◽  
Author(s):  
Nicolás S. Magner ◽  
Jaime F. Lavin ◽  
Mauricio A. Valle ◽  
Nicolás Hardy
Keyword(s):  
Spanning Tree ◽  
Predictive Power ◽  
Minimum Spanning Tree ◽  
Financial Networks ◽  
Order Effects ◽  
Structural Factors ◽  
Financial Variables ◽  
Road Map ◽  
Daily Returns

This investigation connects two crucial economic and financial fields, financial networks, and forecasting. From the financial network’s perspective, it is possible to enhance forecasting tools, since econometrics does not incorporate into standard economic models, second-order effects, nonlinearities, and systemic structural factors. Using daily returns from July 2001 to September 2019, we used minimum spanning tree and planar maximally filtered graph techniques to forecast the stock market realized volatility of 26 countries. We test the predictive power of our core models versus forecasting benchmarks models in and out of the sample. Our results show that the length of the minimum spanning tree is relevant to forecast volatility in European and Asian stock markets, improving forecasting models’ performance. As a new contribution, the evidence from this work establishes a road map to deepening the understanding of how financial networks can improve the quality of prediction of financial variables, being the latter, a crucial factor during financial shocks, where uncertainty and volatility skyrocket.

scholarly journals General election effect on the network topology of Pakistan’s stock market: network-based study of a political event

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Bilal Ahmed Memon ◽  
Hongxing Yao ◽  
Rabia Tahir
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Spanning Tree ◽  
Oil And Gas ◽  
Minimum Spanning Tree ◽  
Centrality Measures ◽  
Political Event ◽  
Industrial Sectors ◽  
General Elections ◽  
Key Nodes

AbstractTo examine the interdependency and evolution of Pakistan’s stock market, we consider the cross-correlation coefficients of daily stock returns belonging to the blue chip Karachi stock exchange (KSE-100) index. Using the minimum spanning tree network-based method, we extend the financial network literature by examining the topological properties of the network and generating six minimum spanning tree networks around three general elections in Pakistan. Our results reveal a star-like structure after the general elections of 2018 and before those in 2008, and a tree-like structure otherwise. We also highlight key nodes, the presence of different clusters, and compare the differences between the three elections. Additionally, the sectorial centrality measures reveal economic expansion in three industrial sectors—cement, oil and gas, and fertilizers. Moreover, a strong overall intermediary role of the fertilizer sector is observed. The results indicate a structural change in the stock market network due to general elections. Consequently, through this analysis, policy makers can focus on monitoring key nodes around general elections to estimate stock market stability, while local and international investors can form optimal diversification strategies.

Temporal Variation of the Node Centrality Metrics for Scale-Free Networks

2018 ◽  
pp. 78-97
Keyword(s):  
Temporal Variation ◽  
Closeness Centrality ◽  
The Other ◽  
Centrality Measures ◽  
Degree Centrality ◽  
Eigenvector Centrality ◽  
Scale Free ◽  
Centrality Metrics ◽  
Scale Free Networks ◽  
Free Network

Scale-free networks are a type of complex networks in which the degree distribution of the nodes is according to the power law. In this chapter, the author uses the widely studied Barabasi-Albert (BA) model to simulate the evolution of scale-free networks and study the temporal variation of degree centrality, eigenvector centrality, closeness centrality, and betweenness centrality of the nodes during the evolution of a scale-free network according to the BA model. The model works by adding new nodes to the network, one at a time, with the new node connected to m of the currently existing nodes. Accordingly, nodes that have been in the network for a longer time have greater chances of acquiring more links and hence a larger degree centrality. While the degree centrality of the nodes has been observed to show a concave down pattern of increase with time, the temporal (time) variation of the other centrality measures has not been analyzed until now.

Centrality Measures

2018 ◽  
Author(s):  
Ginestra Bianconi
Keyword(s):  
State Of The Art ◽  
Centrality Measures ◽  
Eigenvector Centrality ◽  
Multilayer Networks ◽  
Comprehensive Description ◽  
Multilayer Network ◽  
Suitable Definition ◽  
Katz Centrality ◽  
Pagerank Centrality

Defining the centrality of nodes and layers in multilayer networks is of fundamental importance for a variety of applications from sociology to biology and finance. This chapter presents the state-of-the-art centrality measures able to characterize the centrality of nodes, the influences of layers or the centrality of replica nodes in multilayer and multiplex networks. These centrality measures include modifications of the eigenvector centrality, Katz centrality, PageRank centrality and Communicability to the multilayer network scenario. The chapter provides a comprehensive description of the research of the field and discusses the main advantages and limitations of the different definitions, allowing the readers that wish to apply these techniques to choose the most suitable definition for his or her case study.

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