Forecasting Stock Trend by Data Mining Algorithm

الموضوعات :

Sadegh Ehteshami ¹ , Mohsen Hamidian ² , Zohreh Hajiha ³ , Serveh Shokrollahi ⁴

1 - Department of Accounting, Kish International Branch, Islamic Azad University-South Tehran, Tehran, Iran
2 - Department of Accounting and Economic, South Tehran Branch, Islamic Azad University, Tehran, Iran
3 - Young Researcher and Elite club, East Tehran Branch, Islamic Azad University, Tehran, Iran
4 - Department of Accounting and Economic, South Tehran Branch, Islamic Azad University, Tehran, Iran

تاريخ الإرسال : 02 الإثنين , رجب, 1439 تاريخ التأكيد : 02 الإثنين , رجب, 1439 تاريخ الإصدار : 13 الخميس , جمادى الثانية, 1439

الکلمات المفتاحية: Stock trend forecasting, Random forest algorithm, Decision tree algorithm,

ملخص المقالة :

Stock trend forecasting is a one of the main factors in choosing the best investment, hence prediction and comparison of different firms’ stock trend is one method for improving investment process. Stockholders need information for forecasting firm’s stock trend in order to make decision about firms’ stock trading. In this study stock trend, forecasting performs by data mining algorithm. It should mention that this research has two hypotheses. It aimed at being practical and it is correlation methodology. The research performed in deductive reasoning. Hypotheses analyzed based on collected data from 180 firms listed in Tehran stock exchange during 2009-2015. Results indicated that algorithms are able to forecast negative stock return. However, random forest algorithm is more powerful than decision tree algorithm. In addition, stock return from last three years and selling growth are the main variables of negative stock return forecasting.

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