News Analytics

Proven track record

Orthogonal to traditional investment factors

Since 2003, RavenPack has pioneered investment-grade sentiment analysis in financial services. We do not believe in “one size fits all” and have developed multiple sentiment techniques where some leverage millions of rule sets while others use sophisticated machine learning algorithms.

Rich metadata that gives meaning to unstructured public information

Every news story is automatically tagged with topic tags including entities and event categories. RavenPack can recognize over 12 Million named entities including global companies across all industries, both public and private sectors, individuals, executives, insiders and influencers, geographic locations, products, and services. Our proprietary taxonomy covers more than 7,000 different event topics.

More than 40,000 sources of news and social media in 13 languages

Full historical and real-time updates from premium sources including Dow Jones, Wall Street Journal, Barrons, MT Newswires, Benzinga, among others. Our web content captures local, regional, and national newspapers and reputable blogs and content aggregator sites.

Instantly find the relevance, novelty, and impact of news

For every entity and event detected in a story, RavenPack provides advanced analytics including relevance scoring, novelty tracking, and impact analysis. In addition, temporal data provides useful dates for when events take place.