An Attempt To Predict The Daily And Monthly Prices Of Public Shareholding Companies Traded In The Palestinian Stock Exchange (PEX)

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Hamdan, Basheer
Abushihab, Sondos
Daraghmeh, Ghadeer
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The project aims at trying to predict the daily and monthly prices of the public shareholding companies in the Palestinian financial market as accurately as possible using the data history of these companies, in addition to trying to identify the best sectors in the market to invest in. The daily and monthly prices were forecasted using a tool that fully depends on neural network technology, the use of return on investment (ROI) equations to determine the expected return on investment in each sector (profit and loss), and the determination of the appropriate investment and risk profile. The project demonstrates the best way to use, arrange and purify the data to obtain the best results, and how to employ the results for individual investors through the accuracy of the technology used, with the introduction of intuition and experience during the investment process.