Wouldn’t it be great if we could teach a computer to perceive the underlying feeling of a text and exploit that information in stock price forecasting? Are there words that have a more significant influence on the daily stock price change? This research study addresses these questions in the context of stock price forecasting based on news sentiment analysis, using a quantitative trading system. Thanks to increasing openness and availability of electronic information of last years, several types of research addressed the usage of financial text news to sharpen to the best stock price prediction. However, what makes unique and challenging our work is the scale to which this analysis was applied.