Adopting centrality measure models in visualized financial datasets

Jie Hua*, Guohua Wang, Youquan Xu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

1 Citation (Scopus)

Abstract

The financial data is complex to analyse due to its complicated relationships and multiple attributes. Centrality measure models from the SNA (Social network analysis) can show the most critical variables in a network, and graph layouts can be produced to represent not only data networks but also the relations among data entries. To the best of our knowledge, there is no work that has been tried on the Australian stock market based on the combination of those two methods mentioned above so far. This study adopts centrality measure methods and a graph drawing algorithm (force-directed) to offer users big pictures and detailed views, comes with ranking factors based on weighted degree, pagerank and eigenvector metrics. The outcomes show that the methodology can produce clear graph layouts of the stock's social network, identify the central stocks (represent through features such as node colour and size) and the business sectors they belong to. This study may assist stakeholders with grasping deep insight from the complex financial datasets, and another angle of view to adjust future investments accordingly.

Original languageEnglish
Title of host publication2019 International Conference on Image and Video Processing, and Artificial Intelligence
EditorsRuidan Su
Place of PublicationBellingham, Washington
PublisherSPIE
Pages1-6
Number of pages6
ISBN (Electronic)9781510634107
ISBN (Print)9781510634091
DOIs
Publication statusPublished - 2019
Externally publishedYes
Event2019 2nd International Conference on Image and Video Processing, and Artificial Intelligence, IVPAI 2019 - Shanghai, China
Duration: 23 Aug 201925 Aug 2019

Publication series

NameProceedings of SPIE
PublisherSPIE
Volume11321
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

Conference2019 2nd International Conference on Image and Video Processing, and Artificial Intelligence, IVPAI 2019
Country/TerritoryChina
CityShanghai
Period23/08/1925/08/19

Keywords

  • Centrality Measure
  • Social Network Analysis
  • Visual Analytics
  • Force-directed Algorithms

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