المصدر: | مجلة الدراسات والبحوث التجارية |
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الناشر: | جامعة بنها - كلية التجارة |
المؤلف الرئيسي: | Ramadan, Mervat M. (Author) |
مؤلفين آخرين: | Eltelbany, Dina S. (Co-Author) , Soliman, Mohab (Co-Author) |
المجلد/العدد: | س43, ع3 |
محكمة: | نعم |
الدولة: |
مصر |
التاريخ الميلادي: |
2023
|
الشهر: | سبتمبر |
الصفحات: | 275 - 285 |
ISSN: |
1110-1547 |
رقم MD: | 1551503 |
نوع المحتوى: | بحوث ومقالات |
اللغة: | الإنجليزية |
قواعد المعلومات: | EcoLink |
مواضيع: | |
كلمات المؤلف المفتاحية: |
Data Mining | Stock Market | Regression | Neural Network
|
رابط المحتوى: |
المستخلص: |
Finding effective ways to summarise and visualize stock market data so that people or institutions can use it to make investment decisions is one of the most significant problems in modern finance. The stock market generates a massive amount of valuable data, which has drawn researchers to investigate this problem domain using various methodologies. Long-term, intensive research on these issues was motivated by significant potential benefits. The significance of its applications and the growing information generation have made data mining research very appealing. An overview of the use of data mining techniques, including regression and neural networks, in the stock market, is given in this paper. |
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ISSN: |
1110-1547 |