Source: Dow Jones
Dow Jones today introduced News Analytics, a series of product solutions to help traders, quantitative analysts and risk managers build better, more predictable trading models based on news sentiment.
News sentiment analytics quantify the impact of market-moving news, in real time or coupled with historical news models.
For more information about news analytics and how it is used by institutional traders, view this video http://bit.ly/NewsAnalytics.
News Analytics combines Dow Jones' world-class business news content with key technology partners including Alexandria, Digital Trowel, RavenPack and SemLab. Dow Jones has created a series of options to suit a wide range of content, technology and analysis preferences in the market and best support the development of clients' long- and short-term models and risk strategies.
"Machine-readable news and news sentiment are established trading tools, but there have been significant leaps forward in the use and the sophistication of algo trading and sentiment models, coupled with advances in low-latency news delivery," said Rob Passarella, vice president, Dow Jones Financial Markets. "Given the interest we have seen from clients in our elementized news and news sentiment products, we developed integrated product and technology solutions that cover the gamut of trading models and delivery options."
News Analytics features and partners include:
Dow Jones Lexicon - Proprietary sentiment dictionary used to create custom sentiment models
Alexandria - Sentiment assessment for any asset class with advanced language capabilities
Digital Trowel - Sentiment analytics using human-developed rules-based learning and machine-based learning
RavenPack - News analytics featuring relevance, novelty, event and sentiment detection
SemLab - Semantic analysis platform with customizable news analysis and sentiment solutions
Dow Jones, a leader in news analytics and machine-readable news, launched the first machine-readable news feed for institutional traders, the Elementized News Feed, in 2007 and the first trading tool to convert news content into actionable data for trading models, Lexicon, in 2010.
Interest in unstructured data in trading has been growing over the last several years, largely driven by sentiment analytics. In 2008, 2% of the market used unstructured data, but now 35% of firms are exploring the area, according to Aite Group.