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 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 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.

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.

Audit Committee Effectiveness Among Malaysian Listed Companies

2020 ◽  
Author(s):  
Shamsul Nahar Abdullah ◽  
Ku Nor Izah Ku Ismail
Keyword(s):  
Corporate Governance ◽  
Audit Committee ◽  
Stock Exchange ◽  
Listed Companies ◽  
The Other ◽  
Interactive Effects ◽  
Committee Chairman ◽  
Kuala Lumpur ◽  
Political Costs ◽  
Leadership Structure

This study investigates further the previous paper by Shamsul Nahar and Al-Murisi (1997) by examining the interactive effects of the variables in that paper and introducing other variables associated with corporate governance and political costs. The present study postulated that percentage of external directors on audit committee interacted with the presence of an accountant on audit committee and with the number of years an audit committee in existence, respectively, to influence audit committee effectiveness. The study also posited that the interaction of the presence of an accountant on audit committee and the number of years an audit committee in existence positively and significantly influenced audit committee effectiveness. Addition. ally, the roles of leadership structure, audit committee chairman, and a firm's size on audit committee effectiveness were also investigated. Using a multiple regression from a sample consisting the Kuala Lumpur Stock Exchange listed companies, results showed that only a firm's size significantly influenced audit committee effectiveness in the predicted direction. Other variables, on the other hand, did not show any significant influence on audit committee effectiveness.  

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.

scholarly journals ANALISIS PENGARUH INDEKS HARGA SAHAM GABUNGAN REGIONAL ASIA TERHADAP INDEKS HARGA SAHAM GABUNGAN INDONESIA

2018 ◽  
Vol 1 (2) ◽  
pp. 148
Author(s):  
Widodo Widodo
Keyword(s):  
South Korea ◽  
Significant Influence ◽  
Stock Exchange ◽  
Composite Index ◽  
Stock Index ◽  
Kuala Lumpur ◽  
Korea Strait ◽  
Independent Variables

ABSTRACTThe aims of this research is to analyze the influence of NIKKEI 225 Index (^N225), HANG SENG Index (^HSI), KOSPI Index (^KS11), Strait Times Index (^STI), and Kuala Lumpur Stock Exchange (^KLSE) simultaneously and partially in Jakarta Composite Index (^JKSE) during 2009 to 2017. Method of multiple linier regression with significant level 0,05 using STATA 10 program. The populations and samples was used this research is stock index on ASIA regional (NIKKEI 225 (Japan), HANG SENG Index (Hongkong), KOSPI (South Korea), Strait Times Index (Singapore), Kuala Lumpur Stock Exchange (Malaysia), and Jakarta Composite Index (Indonesia)) was conducted during January 2009 to May 2017. Results of this research simultaneously model for all independent variables are influence to dependent variable. However, parcially model ^N225, ^KS11 and ^KLSE variables positive and significant influence to ^JKSE variable. Whereas ^HSI and ^STI variable are not effect to ^JKSE variable during January 2009 to May 2017.Keywords: JKSE; N225; HSI; KS11; STI; KLSE.

Brokerage fee, ownership expropriation and earnings management of Malaysian property companies

2018 ◽  
Vol 36 (4) ◽  
pp. 461-482 ◽  
Author(s):  
Lik Jing Ung ◽  
Rayenda Khresna Brahmana ◽  
Chin-Hong Puah
Keyword(s):  
Real Estate ◽  
Earnings Management ◽  
Stock Exchange ◽  
Real Estate Industry ◽  
Kuala Lumpur ◽  
Probit Regression ◽  
Content Type ◽  
The Real Estate ◽  
Report Data ◽  
The Relationship

Purpose The purpose of this paper is to investigate whether real estate companies manipulate their earnings through the brokerage fee across ownership expropriation or not. Design/methodology/approach This study considers Kuala Lumpur Stock Exchange listed real estate firms to investigate how the brokerage fee in the real estate industry might affect the earnings management of firms across its ownership expropriation. Using annual report data, the authors investigate the associations over a panel for the period 2008−2012. Robust panel regression is used to divulge the probability values with reference by probit regression. Findings Overall, the results show that high brokerage fees would drive more events of earnings management and that, generally, the ownership concentration among Malaysian real estate firms significantly affects the earnings management of the firms. Practical implications This study shows that firm profitability and brokerage fees enhance the probability of firm’s earnings management. A low brokerage fee would reflect low revenue to the company. Therefore, management would opt to manipulate earnings in order to overstate earnings, which garners more interest from investors. Originality/value Real estate values in Malaysia have climbed steadily over the years due to a combination of reasons giving companies a higher brokerage fee. Earnings management has become a big issue for property investors. The study demonstrates the relationship between earnings management and brokerage fee across ownership expropriation which can be considered by shareholders in their own strategic planning and investors in their own investing.

Clique Size and Centrality Metrics for Analysis of Real-World Network Graphs

2019 ◽  
pp. 1183-1198
Author(s):  
Natarajan Meghanathan
Keyword(s):  
Real World ◽  
Random Network ◽  
Maximal Clique ◽  
Closeness Centrality ◽  
Node Degree ◽  
Degree Centrality ◽  
Eigenvector Centrality ◽  
Scale Free ◽  
Centrality Metrics ◽  
Free Network

The authors present correlation analysis between the centrality values observed for nodes (a computationally lightweight metric) and the maximal clique size (a computationally hard metric) that each node is part of in complex real-world network graphs. They consider the four common centrality metrics: degree centrality (DegC), eigenvector centrality (EVC), closeness centrality (ClC), and betweenness centrality (BWC). They define the maximal clique size for a node as the size of the largest clique (in terms of the number of constituent nodes) the node is part of. The real-world network graphs studied range from regular random network graphs to scale-free network graphs. The authors observe that the correlation between the centrality value and the maximal clique size for a node increases with increase in the spectral radius ratio for node degree, which is a measure of the variation of the node degree in the network. They observe the degree-based centrality metrics (DegC and EVC) to be relatively better correlated with the maximal clique size compared to the shortest path-based centrality metrics (ClC and BWC).

Clique Size and Centrality Metrics for Analysis of Real-World Network Graphs

2018 ◽  
pp. 6507-6521
Author(s):  
Natarajan Meghanathan
Keyword(s):  
Real World ◽  
Random Network ◽  
Maximal Clique ◽  
Closeness Centrality ◽  
Node Degree ◽  
Degree Centrality ◽  
Eigenvector Centrality ◽  
Scale Free ◽  
Centrality Metrics ◽  
Free Network

We present correlation analysis between the centrality values observed for nodes (a computationally lightweight metric) and the maximal clique size (a computationally hard metric) that each node is part of in complex real-world network graphs. We consider the four common centrality metrics: degree centrality (DegC), eigenvector centrality (EVC), closeness centrality (ClC) and betweenness centrality (BWC). We define the maximal clique size for a node as the size of the largest clique (in terms of the number of constituent nodes) the node is part of. The real-world network graphs studied range from regular random network graphs to scale-free network graphs. We observe that the correlation between the centrality value and the maximal clique size for a node increases with increase in the spectral radius ratio for node degree, which is a measure of the variation of the node degree in the network. We observe the degree-based centrality metrics (DegC and EVC) to be relatively better correlated with the maximal clique size compared to the shortest path-based centrality metrics (ClC and BWC).

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