Nowadays, information, collected by many institutions and organizations is stored in the form of data stacks. Data mining is a process that can make estimates using data stored in databases. Data mining in stock markets is as advantageous as many other markets in terms of gaining competitive advantage. In this study, a data set was prepared considering the daily increase, decrease and steady state of stocks traded in Istanbul Stock Exchange. By using this dataset, it is aimed to be able to create meaningful clustering and to analyze the clusters formed in terms of sector and business. In this direction, 134 firms using the "maximization of expectation" algorithm, which is one of the data mining process clustering method algorithms, are divided into three groups as "low", "medium level" and "high" stocks. As a result, the clusters, are interpreted in terms of sector and business.
Primary Language | Turkish |
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Journal Section | Research Articles |
Authors | |
Publication Date | December 30, 2018 |
Submission Date | October 11, 2018 |
Acceptance Date | December 17, 2018 |
Published in Issue | Year 2018 |