New forecasting model to predict the winner of the 2020 U.S. election
July 2020 - Our portfolio company RavenPack has launched a free and publicly available monitor offering projections and analysis about the upcoming U.S. election.

Our portfolio company RavenPack has launched a free and publicly available monitor offering projections and analysis about the upcoming U.S. election. Users can download RavenPack’s election data, embed the full dashboard or widgets on their website, and subscribe to regular insights on the U.S. election: RavenPack election monitor.

The monitor is based on a forecasting model that was successful in predicting four of the five previous U.S. presidential elections. An alternative to polls, this new approach uses sentiment analysis and media attention to forecast election results.

“Our news-driven methodology offers an alternative angle to traditional forecasting approaches, such as polls or surveys, and summarizes the complexities of the current political and socio-economic environment in the United States,” says Armando Gonzalez, CEO of RavenPack. “We thought the U.S. presidential election was an ideal opportunity to showcase the power of alternative data on broader use cases than the financial applications for which most of our clients use our data and technology.”

Enquiries
For enquiries, please contact:
Per Roman, Managing Partner, GP Bullhound at per@gpbullhound.com
Armando Gonzalez, CEO, RavenPack at info@ravenpack.com

About GP Bullhound
GP Bullhound is a leading technology advisory and investment firm, providing transaction advice and capital to the world’s best entrepreneurs and founders. Founded in 1999, the firm today has offices in London, San Francisco, Stockholm, Berlin, Manchester, Paris, Hong Kong, Madrid and New York. For more information, please visit www.gpbullhound.com, or follow on Twitter @GPBullhound.

About Ravenpack
RavenPack is a leading big data analytics provider for financial services. RavenPack’s platform is used by some of the best performing hedge funds and largest banks worldwide. RavenPack uses AI to turn highly fragmented unstructured content into organised structured data for easier analysis and deployment in financial applications. The firm has a team of more than 100 people and offices in New York City and Marbella, Spain. www.ravenpack.com

Region
USA