Overview

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Key Features

• Catalyst Detection: Each article is enriched with a machine-generated catalyst summarizing the event’s potential market impact — ideal for alerting or ranking.
• Security Mapping: News stories are tagged with detailed security-level data including FIGIs, share class identifiers, tickers, and exchange metadata.
• Ticker Normalization: Stories affecting multiple securities are de-duplicated and resolved to composite tickers and exchanges for precise targeting.
• Multichannel Attribution: News is classified by type (e.g., gainers/losers) and linked with other relevant datasets like press releases, ratings, and transcripts.
• Rich Metadata: Includes timestamps, headline content, logo thumbnails, and internal IDs for seamless frontend rendering or record linkage.
• Query Flexibility: Filter by ticker, share class FIGI, type, ID, and pagination — with support for batch use cases or real-time feed polling.

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Coverage

• Universe: U.S.-listed stocks including ADRs, common stock, and multi-exchange listings across NASDAQ, NYSE, OTC, and regional venues.
• Content Types: Market movers, earnings reactions, leadership changes, FDA decisions, trial results, and more.
• Enrichment: Catalysts are auto-detected for high-signal headlines, enabling low-latency event tracking and news-based trading models.

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Use Cases

• Trigger portfolio or watchlist alerts based on real-time catalyst-based headlines
• Feed high-impact news into trading models, dashboards, or mobile apps
• Backtest news-based strategies using timestamped, security-linked data
• Power personalized newsfeeds or event-driven content sections for investor portals
• Detect spikes in correlated data like price movement, social sentiment, or analyst revisions