TY - JOUR
T1 - Applying hybrid graph drawing and clustering methods on stock investment analysis
AU - Zreika, Mouataz
AU - Varua, Maria Estela
PY - 2016
Y1 - 2016
N2 - 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.
AB - 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.
KW - clustering
KW - investment analysis
KW - stocks
UR - http://handle.uws.edu.au:8081/1959.7/uws:34341
UR - http://waset.org/publications/10003887/applying-hybrid-graph-drawing-and-clustering-methods-on-stock-investment-analysis
M3 - Article
SN - 2010-376X
VL - 10
SP - 689
EP - 698
JO - International Journal of Social, Behavioral, Educational, Economic, Business and Industrial Engineering
JF - International Journal of Social, Behavioral, Educational, Economic, Business and Industrial Engineering
IS - 3
ER -