Armando Gonzalez, RavenPack
New York - RavenPack, the provider of big data analytics to financial institutions, has 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 without the need for a team of data scientists.
RavenPack transforms 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.
RavenPack allows discretionary and fundamental investors to:
- Construct complex trading signals using a simple user interface to more easily detect market-moving events. Investors now can easily plug big data into more traditional strategies.
- Identify market trends and patterns visually by charting sentiment indicators alongside pricing data to make better predictions.
- Download signals into popular tools used by analysts and traders including Excel, R, Python, and Matlab.
"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."