Commenced in January 2007
Paper Count: 30673
Applying Hybrid Graph Drawing and Clustering Methods on Stock Investment Analysis
Abstract:Stock investment decisions are often made based on current events of the global economy and the analysis of historical data. Conversely, visual representation could assist investors’ gain deeper understanding and better insight on stock market trends more efficiently. The trend analysis is based on long-term data collection. The study adopts a hybrid method that combines the Clustering algorithm and Force-directed algorithm to overcome the scalability problem when visualizing large data. This method exemplifies the potential relationships between each stock, as well as determining the degree of strength and connectivity, which will provide investors another understanding of the stock relationship for reference. Information derived from visualization will also help them make an informed decision. The results of the experiments show that the proposed method is able to produced visualized data aesthetically by providing clearer views for connectivity and edge weights.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1112033Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1261
 Cindy Wang. 2014. Investing 101: How to Analyze Stock Market Trends. (ONLINE) Available at: http://blog.sprinklebit.com/investing-101-how -to-analyze-stock-market-trends/. (Accessed 13 July 15).
 Omote, H. & Sugiyama, K. 2007, Force-Directed Drawing Method for Intersecting Clustered Graphs, APVIS 2007, 6th International Asia-Pacific Symposium on Visualization 2007, 5-7 February 2007, Sydney, Australia, pp.85-92
 Huang, X. & Lai, W., 2005, clustering graphs for visualization via node similarities. J. Vis. Lang. Comput. 17, 3 (June 2006), pp. 225-53. Elsevier Ltd.
 Huang, M., Nguyen, Q. V., A space efficient clustered visualization of large graphs Image and Graphics, 2007. ICIG 2007. Fourth International Conference on, pp. 920-27
 Huang, M.L., & Nguyen, Q.V. 2007, Navigating Large Clustered Graphs with Triple-Layer Display, 11th International Conference Information Visualization, 2-6 July 2007, Zürich, Switzerland, pp. 684-92.
 Sarkar, M. & Brown, M.H. 1994, ‘Graphical fisheye views’, Communications of the ACM, Volume 37 Issue 12, pp. 73–83.
 Huang, M.L., Eades, P. & Wang, J. 1998, On-line animated visualization of huge graphs using a modified spring algorithm, Journal of Visual Language and Computing, no. vl980093, pp. 623-45.
 Huang, M.L., Eades, P. & Cohen, R.F. 1998, Webofdav – navigating and visualizing the web on-line with animated context swapping, Computer Networks and ISDN Systems, 30(1), pp. 638-42.
 Nguyen, Q.V. & Huang, M.L. 2005: EncCon: an approach to constructing interactive visualization of large hierarchical data. Information Visualization 4(1): 1-21.
 Qiu, M., Zhang, K., Huang, M., 2006, Usability in mobile interface browsing, Web Intelligence and Agent Systems, Vol.4 (1), pp. 43-59, IOS Press.
 Nguyen, Q. V. and Huang, M. L., A focus+ context visualization technique using semi-transparency, The Fourth International Conference on Computer and Information Technology, 2004. CIT'04, pp. 101-08.
 Brandes, U., Delling, D., Gaertler, M., Gorke, R., Hoefer, M., Nikoloski, Z., Wagner, D., On Modularity Clustering, Knowledge and Data Engineering, IEEE Transactions on, pp. 172 - 88 Volume: 20, Issue: 2, Feb. 2008.
 Battista, G.D., Eades, P., Tamassia, R. & Tollis, I.G. 1999, Graph drawing algorithms for the viisualization of graphs, Prentice-Hall, New Jersey, USA.
 Eades, P., A heuristic for graph drawing. Congress Numerantium, 42:149-160, 1984.
 Lin, C.C., Yen, H.C. 2005, A New Force-Directed Graph Drawing Method Based on Edge-Edge Repulsion, Ninth International Conference on Information Visualisation, 6-8 July 2005, London, UK, pp.329-24
 Battista, G.D., Eades, P., Tamassia, R. & Tollis, I.G. 1999, Graph drawing algorithms for the visualization of graphs, Prentice-Hall, New Jersey, USA.
 Lin, C.C. & Yen, H.C. 2008, A new force-directed graph drawing based on edge-edge repulsion, 9th International Conference on Information Visualization IV2008, 6-8July, London, England, pp. 329-34.
 Hua, J. & Huang M.L. (2013). Improving the Quality of Clustered Graph Drawing through a Dummy Element Approach. In Computer Graphics, Imaging and Visualization (CGIV), 2013 10th International Conference. Macau, 6-8 Aug. pp. 88-92.
 Hua, J., Huang, M.L & Nguyen, Q.V, (2014). Drawing Large Weighted Graphs Using Clustered Force-Directed Algorithm. In Information Visualisation (IV), 2014 18th International Conference on. Paris, 16-18 July 2014. Paris: IEEE. pp. 13-17.
 Yahoo finance. 2016. Yahoo!7 Finance. (ONLINE) Available at: https://au.finance.yahoo.com/q. (Accessed 11 February 16).