Financial News Analysis for Moroccan Stock Trend Predictions


  • El Bousty Hicham
  • Krit Salah-Ddine


This article aims to predict Moroccan stock trends based on financial news articles. Data are collected from All news collected for a single stock are lower to fit any machine learning algorithm, thus they are all combined for the training and the test issues. In these experiments we used 1061 articles published from 2015 to 2019. We compared performance of Support Vector Machine (SVM), Naïve Bayes, k Nearest Neighbors (KNN) and Decision Tree algorithms. Comparisons are performed first on news headlines and then on news corpus. Later we tried to enhance accuracy of the results using a specific dictionary-based approach. We attend 60% accuracy which is an acceptable rate in this context of the Moroccan market. We also inspected the reactivity of the Moroccan market to the publication of financial news by varying the forecasting scope.Results shows that the Moroccan Market react better to news publication four days later.