RavenPack | September 20, 2017
New enhancements and functionality empowers wider investment community to construct trading signals from big data
NEW YORK - September 20, 2017 -
, the leading provider of big data analytics to financial institutions, today launched a new service to create trading signals from big data including the web, news, social media, regulatory filings, and more. Primarily utilized by quantitative hedge fund and asset managers, the new enhancements now allow more traditional investors to use the RavenPack platform to apply the techniques employed by the most sophisticated funds without the need for a team of data scientists.
Today, data-driven traders have to sift through thousands of data-sets to extract the information that matters most to them. RavenPack simplifies the process for firms by transforming unstructured big data sets, such as traditional news and social media, into structured data, including sentiment and media attention indicators, to help financial services firms to interpret business and macroeconomic trends and improve performance.
The new enhancements to RavenPack’s platform meet the market's demand from traditional investors that are turning increasingly quantamental by combining fundamental data and other data sources. RavenPack clients now can more easily use sentiment analysis and convert market-moving events such as economic indicators, earnings releases, and M&A reports into trading signals, further enabling investors to make more informed and timely investment decisions.
Now more self-service and automated, RavenPack allows discretionary and fundamental investors to:
The chart shows a 7-day moving average of the event sentiment score for Amazon Inc. alongside Amazon’s stock price while the bar-chart at the bottom shows the daily news volume for Amazon.
“The ability to build custom signals on the RavenPack platform is a game-changer for discretionary and fundamental investors who value logic and facts,” said Armando Gonzalez, CEO of RavenPack. “Until now, our core tools and techniques have only been available to the largest quantitative hedge-funds and investment banks. Creating signals from big data sources is now simple and intuitive - and accessible for most financial professionals.”
RavenPack launched its self-service data and visualization platform in March of this year. The platform enables clients to query and visualize big data on thousands of entities including companies, commodities, currencies, organizations, people and products.
In early 2017, the company secured $5 million backing from Draper Esprit (AIM:GROW, ESM: GRW), a leading venture firm involved in the creation, funding and development of high-growth technology businesses.
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