This solution classifies financial news headlines into positive, negative and neutral sentiments. It uses text analysis, natural language processing, machine learning techniques to predict the sentiment classes. This solution is built around specialized vocabulary encountered in finance and economics. It can be used to identify sentiments of financial headlines and statements from the perspective of potential investors and stakeholders.