RavenPack
News Analytics
Insights generated systematically from over 22,000 sources of news and social media
Sentiment Analysis
Relevance Scoring
Novelty Tracking
Temporal Scoring
Topic Tagging
How can firms benefit from News Analytics?
Reduce risk and increase efficiency by systematically incorporating the effects of public information into your workflows.
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 300,000 named entities including companies, people, and geographical locations. Our proprietary taxonomy covers more than 6,000 different event topics.
More than 22,000 sources of news and social media
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.
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 300,000 named entities including companies, people, and geographical locations. Our proprietary taxonomy covers more than 6,000 different event topics.
More than 22,000 sources of news and social media
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.
Use Cases
More than 70% of the best performing quantitative hedge funds and asset managers use RavenPack News Analytics for alpha generation and risk management.
Investing & Trading
Derive signals to support trading models across all asset classes, trading styles and frequencies
Portfolio Management
Improve asset allocation decisions by measuring sentiment on markets, sectors, and asset classes
Research & Analysis
Forecast stock, sector, market and global economic outlooks
Algorithmic Trading
Predict liquidity, volatility, and directional movements caused by news events
Risk Management & Compliance
Detect market abuse, mitigate risk quickly when events happen, and build early-warning systems
Trade Surveillance
Conduct pre-trade and post-trade analysis by connecting trading activity to key news announcements
Latest Research
RavenPack News Analytics is the most published alternative dataset out there. Here are some of the latest research studies available.
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