Exploring the Relationship Between News Articles and Stocks Market Movements: A Sentiment Analysis Perspective

Research has shown that sentiments in news headlines and articles have an effect on stock price movement. Thus, exploring this correlation can help with stock price prediction. In this work, we aim to explore the causality between news articles extracted from Reddit News and stock prices, downloaded from Yahoo Finance. ARIMA model is utilized and SMAPE and MSE values were calculated to ascertain which model fits the given data. In addition, correlations between sentiments extracted from news headlines and stock prices were calculated. Moreover, Random Forest, Support Vector Machine and Naïve Bayes algorithms were used to determine the best model to predict stock market movements while considering news sentiments polarity as an additional predictor. Comparing models’ accuracies show that Random Forest perform the best, scoring 66%. Findings based on daily statistics show that there is indeed correlation between news articles and stock prices, although it is not very strong.