Using Markov Chains Model and Decision Tree Classifier to Predict the Behavior of Palestinian Stock Market Prices - Case Study :Paltel

Abstract

Predicting the behavior of stock market prices has been one of the most poplular topic interest for researchers due to its complex and dynamic nature.In this thesis Markov Chains Model and Decision Tree Classifiers applied to forecast and analyse the behavior of the Palestinian Stock Market prices- case study :Paltel. For this purpose, 243 days includus the daily opening price, volume and number of deals covering the period from 2nd January 2019 till 31th December 2019 of Paltel company were collected from Palestine Exchange .At the beginning the Markov Chain model was applied depending on the opening price where Markov Chain model is a probability model depend on transition probability matrix and initial