Applying Data Visualization Techniques for Stock Relationship Analysis

JIE HUA, Mao Lin Huang, Mouataz Zreika, Guohua Wang

Abstract


Decision making in stock investment is often made based on current events in the market and the analysis of historical data on specific stocks. Besides, similar rates of price changing over a long-term period on different stocks may indicate potential connections between those listed corporations. The proposed methodology applies the force-directed algorithm and time-series chart to offer stakeholders capability to gain deeper insights initiative on potential relationships between stocks comes with less human interventions. Hence to assist in future decision making on stock investment via graph layouts.

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