Earnings Intelligence

Uncover more alpha before, during, and after earnings announcements, from the combination of 4 proven sources of market insights.

The Earnings Intelligence factor incorporates insights from Earnings News, Transcripts, Insider Transactions, and (for US companies) Earnings Dates, into a unified factor delivering a comprehensive and alternative perspective on a company’s outlook.

Use Cases

Discretionary and quantitative investors can use these factors to build signals that:

Factor Performance

By leveraging the different nature, and orthogonal value, of the various Earnings Intelligence factor families, the RavenPack Earnings Intelligence Factor provides more risk diversification and an overall more robust performance across different universes and holding periods.

The performance results of the Earnings Intelligence factor across six typical trading universes is presented below as cumulative log returns, using a fixed portfolio size, showing robust performance over time across all universes and holding periods, and minimal exposure to drawdowns during major bear market periods, such as 2008 and 2022.

Factor Components

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UNDER THE HOOD

Computing Earnings Intelligence Factors

The Factor is the outcome of a multi-step process including:

Signal Component Aggregation

Individual factors from Earnings News, Transcripts, and Earnings Dates (US only) are aggregated for each company. More information on the construction of individual factors can be found on their respective documentation.

Normalization and overlay

A cross-sectional daily normalization is then implemented. Finally, Insider Transactions information is integrated to adjust factors (overweight or underweight) based on the net insider transaction volume executed between consecutive earnings announcements.

Company Factors Facts
Purpose
  • Extract alpha
  • Mitigate portfolio risk
Frequency6 times daily at the open & close
in New York, Paris, and Tokyo
HistorySince 2007
Universe100,000 Listed Companies
Content
  • When the factor was produced
  • The company, as name and RavenPack entity identifier.
  • Exponential smoothing decay — the number of days used for exponential smoothing with 1, 7, and 30 days provided.
  • Moving average window for the data calculation: 90 or 180 days.
  • Factor name — The name of the factor: EARNINGS_INTELLIGENCE.
  • Factor score — the numerical score value representing the computed factor for the given entity.
Delivery RavenPack, Snowflake

Access the Earnings Intelligence Factor


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