Ensemble time series models for stock price prediction and portfolio optimization with sentiment analysis

The work introduces a hybrid ensemble model that combines conventional stock market prediction models with sentiment analysis of news articles in order to improve the accuracy of predictions, achieving an impressive average prediction accuracy of 91.89% where the model was evaluated on ten stocks and surpassed the performance of current models.