Machine Readable News

Machine readable news is the news-data which is easy to read and process for a computer. News and social media data are available in huge volume but they are unstructured,  therefore it becomes difficult to understand whether a particular news is relevant to a  company, and whether the story is new or not. Machine readable news algorithms break thousands of such news stories, prioritizing their relevance on the basis of simple keywords, author sentiment, and other parameters and deliver them in a special feed along with a sentiment score. In trading, news and sentiments are one of the most important sources of signals for stock selection and trading. A correlation between sentiment scores and stock/index price movements is analyzed using quantitative methods and machine learning techniques which will help a trader to take positions in the market.