The Use of the Regression Tree and the Support Vector Machine in the Classification of the Iraqi Stock Exchange for the Period 2019-2020 - Hesham Ibrahim, Mohamed; Ghalib Jaber, Asmaa (Journal of Economics and Administrative Sciences, 2022)
The financial markets are one of the sectors whose data is characterized by continuous movement in most of the times and it is constantly changing, so it is difficult to predict its trends , and this leads to the need of methods , means and techniques for making decisions, and that pushes investors and analysts in the financial markets to use various and different methods in order to reach at predicting the movement of the direction of the financial markets. In order to reach the goal of making decisions in different investments, where the algorithm of the support vector machine and the CART regression tree algorithm are used to classify the stock data in order to determine the trend of the stock if it is a rising stock or a descending stock .The aim of the research is to classify the financial stock data using five variables where the data of the Iraqi Islamic Bank for investment and development was used where the results showed the accuracy of the algorithm, the support vector machine and the CART algorithm, and their performance was good. Also, the results showed that the Support Vector Machines algorithm is the best when compared with the CART algorithm, using the Classification Error and MSE criteria