MATEC Web Conf.
Volume 76, 201620th International Conference on Circuits, Systems, Communications and Computers (CSCC 2016)
|Number of page(s)||4|
|Published online||21 October 2016|
Applying Moving Objects Patterns towards Estimating Future Stocks Direction
1 Information Systems, Informatics and Computer Science, British University in Egypt
2 Information Systems, Informatics and Computer Science, Helwan University in Egypt
a Corresponding author: Dahab.Galal@bue.edu.eg
Stock is gaining vast popularity as a strategic investment tool not just by investor bankers, but also by the average worker. Large capitals are being traded within the stock market all around the world, making its impact not only macro economically focused, but also greatly valued taking into consideration its direct social impact. As a result, almost 66% of all American citizens are striving in their respective fields every day, trying to come up with better ways to predict and find patterns in stocks that could enhance their estimation and visualization so as to have the opportunity to take better investment decisions. Given the amount of effort that has been put into enhancing stock prediction techniques, there is still a factor that is almost completely neglected when handling stocks. The factor that has been obsolete for so long is in fact the effect of a correlation existing between stocks of the same index or parent company. This paper proposes a distinct approach for studying the correlation between stocks that belong to the same index by modelling stocks as moving objects to be able to track their movements while considering their relationships. Furthermore, it studies one of the movement techniques applied to moving objects to predict stock movement. The results yielded that both the movement technique and correlation coefficient technique are consistent in directions, with minor variations in values. The variations are attributed to the fact that the movement technique takes into consideration the sibling relationship
© The Authors, published by EDP Sciences, 2016
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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