RavenPack Launches New Version of News Analytics Service to Enhance Investing, Trading and Market Surveillance

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7 September 2014
United States

New version builds on RavenPack’s powerful text-mining and event detection technology, identifying more than 2,000 types of geopolitical, macroeconomic and corporate events; a 70% increase over prior version

NEW YORK and LONDON – September 8, 2014 - RavenPack, the top provider of real-time financial news analysis services, today announced the launch of RavenPack News Analytics (RPNA) 4.0, with significant advances in its news analytics and event detection capabilities, enabling quantitative analysts and data scientists to accelerate the discovery of relationships between news and financial markets.

RPNA 4.0 brings new sentiment indicators, farther-reaching event novelty analytics and an expanded taxonomy focusing on macroeconomic and geopolitical risks. New data packages and delivery mechanisms help reduce the time needed to discover and test new strategies or techniques that may enhance alpha generation, mitigate risk or help identify potential market abuse and insider trading.

“Version 4.0 nearly doubles the number of market-moving events we detect, capturing more of the nuances in natural language towards a tradable instrument, hence the potential for increased alpha - or more effective surveillance and risk management,” said Armando Gonzalez, RavenPack’s Chief Executive. “We’re particularly excited by this new version which effectively gives clients the ability to model and test the reaction to macroeconomic and geopolitical news and systematically act upon these developments, in real-time if they so desire.”

RPNA now ingests and analyses unstructured news and opinion from around 19,000 online news and social media sources in real-time. It detects more than 2,000 potentially market-moving events from over 200,000 entities, including more than 34,000 listed companies and 2,500 financially-sensitive organisations. RPNA data consists of raw news analytics for every mention of an entity and indicators summarising sentiment and media attention at an entity level. RavenPack also stores over 14 years of historical data for modelling and back-testing.