Context Analytics' Quantitative News Feed provides predictive news sentiment for quantitative strategies and alpha generation. Leveraging and enhancing our proprietary Natural Language Processing (NLP) technology, this product is designed to streamline the way users consume and analyze financial news.
Comprehensive news analytics with unmatched scale and speed
Sophisticated sentiment analysis and topic categorization across multiple languages
Automatic identification and prioritization of securities discussed in each article
Comprehensive coverage from major news outlets, financial publications, and industry sources
Tag articles with specific themes: M&A, earnings, analyst ratings, and other key events
Sub-second processing and delivery for time-sensitive trading and risk applications
Combine news analysis with proprietary Twitter-based sentiment for enhanced predictive power
Advanced analytics and categorization for actionable insights
Real-time view of news sentiment, topics, and market-moving stories
Monitor article flow and coverage intensity across all sources
Real-time sentiment analysis across positive, negative, and neutral news
Automated tagging and classification of news themes and topics
Transform unstructured headlines into structured trading signals
Proven performance across trading, risk management, and business intelligence
Common questions about the Quantitative News Feed
The Quantitative News Feed is Context Analytics' NLP-driven news sentiment product that converts financial news articles into structured, ticker-tagged sentiment scores for use in systematic trading and research.
CA processes 78,000+ articles per month from 8,000+ news sources, with 24/7 real-time processing.
News sentiment is scored on a proprietary -1 to +1 scale using CA's NLP models.
Articles are tagged by topic based on our rules based NLP, including themes like M&A, earnings, and analyst ratings and tagged at the security level so users can search news by ticker.
The feed offers sub-second processing and delivery, built for time-sensitive trading and risk applications.
Yes. The Quantitative News Feed can be overlaid with CA's Twitter-based S-Factor sentiment for enhanced predictive power, combining two independent alternative data signals.
The feed is delivered as a JSON API over REST, designed for streamlined integration into existing systems.
Common uses include 24/7 risk monitoring, converting headlines into structured trading signals, fundamental research support, and tracking how narratives evolve over time — spanning 2000+ companies across financial and business news.
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