DATA MINING AND ITS IMPACT ON INVESTORS’ DECISIONS: A CASE STUDY IN THE IRAQI FINANCIAL MARKET USING THE RBF MODEL

Authors

  • Amna Shehab Ahmed Al-Hassan A Assistant Lecturer at Al-Nahrain University, College of Business Economics. Baghdad, Iraq.

Keywords:

Data mining, artificial neural networks, RBF model.

Abstract

The research addressed the definition of data mining technology in general and the RBF model in particular and its importance in analyzing financial market data to facilitate investors’ decisions. The data was collected based on the daily and weekly reports of the Iraqi stock market, where the research sought to test a main hypothesis that states that adopting artificial neural network algorithms The radial basis function (RBF) is one of the best data mining algorithms for predicting and analyzing financial indicators for the sample studied. The research reached a set of conclusions, the most important of which is confirming the research hypothesis. Based on this, the researcher recommended the necessity of studying other indicators within a longer period to obtain higher accuracy of the results, as the larger the data sample, the more accurate the techniques used in data mining.

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Published

2024-01-03

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Section

Articles

How to Cite

DATA MINING AND ITS IMPACT ON INVESTORS’ DECISIONS: A CASE STUDY IN THE IRAQI FINANCIAL MARKET USING THE RBF MODEL. (2024). American Journal of Business Management, Economics and Banking, 20, 1-10. https://americanjournal.org/index.php/ajbmeb/article/view/1706