Abstract:

In this study a data mining process is performed in finance sector. During this process, considering closing prices of securities of 10 different banks which are obtained from Istanbul Stock Exchange (ISE) for the period 1990-2010 and some technical indicators which are widely used in some technical analysis of these securities, the changes of gold prices, exchange rate and also some international stock market indicators, some decision trees are built and then decision rules are obtained on the basis of these trees. Applying somedata preprocessing operations on the data, the first stage of the process is completed. Afterward, a classification model, which is also called “predictive model” among other data mining models, is performed on the dataset. Besides, some Multiple Linear Regression Models are applied to reduce the number of attributesand therebyinsignificant ones are removed in the following stages.Finally, selecting some attributes related withthe securities’ regressio

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