RavenPack Factors

Powerful Insights, Streamlined Delivery.

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Access insights that move markets

To make advanced insights more accessible, RavenPack has analyzed terabytes of news articles, filings, and transcripts, to produce actionable sentiment and market-moving factors that work for every investor — from quantitative to discretionary trading. Leverage these factors to:

Explore the RavenPack Factor Library

RavenPack Factors leverage advanced analytics from the systematic processing of unstructured data to capture actionable insights for equities, bonds, and macro markets.

Macro-level Factor Families

C-Level Economic Sentiment Indicator

C-Level Economic Sentiment

Macroeconomic factor to identify business cycles for the U.S. economy. Compiled from the insights of business leaders on the US economy during earnings calls.

1Factor types
7values for these factors per day
Why use it?

To anticipate the most important inflection points in US economic activity and provide a more accurate assessment of the state of the economy.

 Nowcasts

Macroeconomic Nowcasts

Daily predictions of inflation and GDP growth of major economies from the outcome of alternative data-driven models.

4Nowcast factors
4values for these factors per day
Why use it?

To improve the performance of traditional economic nowcasting models both in terms of timeliness and accuracy.

 Nowcasts

Forex Sentiment

Daily Trend-Following and Mean-Reverting trading signals from macro news sentiment across G7 currencies.

2Factor types
10values for these factors per day
Why use it?

As macroeconomic news and geopolitical events increase the volatility in FX markets, sentiment becomes a key component in boosting signals for FX futures strategies.

Company-level Factor Families

Controversy Scores

Controversy Scores

Company-level factors of emerging ESG controversies identified from the systematic analysis of 40,000 news and social media sources.

6Factor types per covered company
213values for these factors per snapshot
Why use it?

To identify stocks and bonds with low controversy profile to capture more alpha and lower risk.

 Controversy Scores

Company News

News sentiment and media attention insights on market-moving events at a document and event levels, 6 times daily.

6Factor types per covered company
390values for these factors per snapshot
Why use it?

Quantify the impact of media coverage for inclusion into strategies and dashboards.

 Earnings Intelligence

Earnings Intelligence

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

5Factor types per covered company
53values for these factors per snapshot
Why use it?

Leverage alpha-generative signals backed by research

Investment decision-making processes are often sophisticated, but integrating additional insights should not be. RavenPack Factors make the output of advanced quantitative models accessible to all investors with several convenient delivery mechanisms including CSV files, as data warehouses on Snowflake, or customizable queries using Python libraries.

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