Credit News

Boost event-driven credit strategies with research-based signals from hard and soft corporate catalysts detected in top reputable sources.

Two factor types are provided:

Use Cases

Credit traders can trade these signals to enhance credit event-driven strategies and alpha capture, and mitigate credit risk:

Factor Performance

The performance of these factors has been backtested against a point-in-time archive of news from September 2015 until February 2024. Long-short credit portfolios for a diverse array of trading scenarios were used. The results highlight the robustness and versatility of the signals across targeted universes. Factors use a mapping of identifiers maintained by RavenPack daily for a comprehensive and up-to-date referencing of available bonds.


Computing Credit News Factors

The Factors are the outcome of a multi-step process including:

Content Collection

RavenPack analyzes textual content from high-reputation sources over 40,000 curated ones to identify credit-related events in news for over 7 millions of companies, including both public-listed and private companies.

Analytics Enrichment

For each corporate catalyst identified, RavenPack applies sentiment analysis to compute credit sentiment scores by matching stories usually categorized by credit analysts as having a positive or negative impact on credit spreads. We retain stories for bond issuers and events co-detected in the headlines of novel content in top reputable sources.

Information Extraction

Documents considered include full articles, news flashes, press releases, and tabular material exclusively from top reputable sources.

Signal Construction

The factors are aggregated until 60 minutes before the credit markets close, and at the event type level of business events from the RavenPack Event Taxonomy. This high level of granularity ensures to isolate individually around 120 types of hard and soft catalysts with specific repricing effects. After aggregation, the credit sentiment scores are exponentially smoothed to control the factor turnover. Our flexible approach involves constructing these daily factors with multiple cutoff times, facilitating the timely capture of alpha across different corporate bond universes throughout each trading day.

Credit News Factors Facts
  • Extract alpha
  • Mitigate Portfolio Risk
HistorySince 2001
UniverseOver 7 million public and private companies.
  • When the factor was produced.
  • The currency, as name and RavenPack entity identifier.
  • Exponential smoothing decay — the number of days used for exponential smoothing with 0 (raw score), 1, 7, and 30 days provided.
  • Factor name — one of the following: Mean Credit Sentiment or Credit Event Volume.
  • Factor score — the computed value for that specific currency.
Delivery RavenPack, Snowflake

Access the Credit News Factors

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