WRDS Expands RavenPack Analytics
February 22, 2021
Research Data Services added RavenPack expanded Analytics data to its offerings.
A part of the Wharton School of the University of Pennsylvania, WRDS provides
global corporations, universities, and regulatory agencies the thought
leadership, data access and insights needed to enable impactful research.
Alternative data has opened innovative pathways to analyze financial, economic
and societal behaviors. Within that growing family of datasets, news analytics
from RavenPack empower researchers to apply quantitative models to time series
by presenting structured insights drawn from large numbers of curated news
sources and business data. Augmented with sentiments and attention scores, these
point-in-time datasets make it possible to identify previously unattainable
Through continuous technological investment and supported by its own team of
data scientists, RavenPack has significantly expanded its event detection and
sentiment scoring capabilities, and this latest dataset is now available to
researchers on WRDS.
correlations, patterns, relevance and influences in time series using
quantitative models across an unprecedented breadth of topics from 25,000+
Explore point-in-time records augmented with sentiment and media attention
scores from 20+ years of historical data.
Search 300,000+ entities and 160,000+ macro entities referenced across all
“We are excited to expand RavenPack’s Analytics offerings,” said Robert
Zarazowski, Managing Director of WRDS. “With extensive research being conducted
in the area of textual analysis, RavenPack brings its latest innovations and
extensive data to our global research community.”
Peter Hafez, Chief Data Scientist at RavenPack commented: “Academic researchers
around the world are increasingly relying on our datasets to produce and publish
outstanding research papers underpinned by our reliable news and sentiment
analytics. The highly anticipated availability of RPA 1.0 on the Wharton
Research portal will stimulate innovative research by unlocking insightful
signals from financial market research to social sciences”.