Prediction of the Closing Price in the Dubai Financial Market: A Data Mining Approach
Closing prices of the financial stock market change daily at the end of each session. These changes happen because of many factors that affect the prices of the stocks. This study attempts to accurately predict closing prices by applying a data mining approach and investigate and identify the most influential factors of Dubai Financial Stock Market prices. The main objective of this study is to help investors plan their future investment opportunities well. Two methods are used in this study: supervised and unsupervised algorithms. The results obtained have shown that the model can predict the closing price using the classification algorithm with accuracy greater than 92% and that the regression algorithm succeeded in predicting the stock prices with a correlation coefficient equal to 0.8889.
|Journal||Data powered by Typeset2016 3rd MEC International Conference on Big Data and Smart City (ICBDSC)|
|Publisher||Data powered by TypesetIEEE|