Minetta Brook™ today announced the integration of the MT Newswires LIVE Briefs® PRO service into its award-winning KNEWSAPP™ solution, a real-time news analytics, monitoring & discovery application for traders & investors. KNEWSAPP is designed to identify investment opportunities and mitigate risk by surfacing highly predictive signals from developing news, tweets, blogs and other business and financial information sources across the globe. Cutting edge computational linguistics combines with machine learning and proprietary algorithms to process information streams in real-time and alert investors to indicative spikes in company, sector and/or market news of specific interest to them.
"Traditional news feeds and search engines emphasize mere timely delivery or readership popularity. The modern investment professional is moving beyond this, to a world where prioritization is based on what’s being written, not how many people are reading it,” said Prabhu Venkatesh, Chief Scientist at Minetta Brook. “By the time a news item is broadly consumed, the opportunity has evaporated. This is where automated content analysis can recognize a piece of news as important before others do thereby providing a significant competitive advantage and more informed decision-making.”
Minetta Brook captures millions of news articles, blog posts and tweets in real-time across 47,000 sources globally. Proprietary velocity algorithms identify and score fast-developing topics related to tickers leveraging machine-learning to drive a unique rating and ranking system designed to deliver actionable investment signals to KNEWSAPP users.
“Integrating MT Newswires’ LIVE Briefs PRO into KNEWSAPP allows us to add another reliable, objective source of real-time financial market news to our detection processes,” said Minetta Brook CEO, Dan Concannon. “With LIVE Briefs PRO, we are improving our ability to connect business intelligence and market intelligence on companies and sectors ahead of the developing story. We connect dots that others don’t know exist.”
Originally founded as Midnight Trader to capture after hours and pre-market news cycles to support extended trading, MT Newswires has become a leading source of full-day market information and reporting. Many of the world’s largest banks, brokerage houses and trading firms rely on MT Newswires’ LIVE Briefs service.
"We're very pleased to be working with Minetta Brook to further enhance their innovative KNEWSAPP solution. Their cultivated and predictive business information analytics combined with our industry leading multi-asset class real time Live Briefs PRO North American newswire creates a complete picture for the investment community," offers Brooks McFeely, MT Newswires' founder and CEO.
In May of last year, Minetta Brook introduced its first version of KNEWSAPP via the Bloomberg Professional service. Propelled by consistently positive user feedback, the firm subsequently launched its KNEWSAPP web-based solution, which led to Minetta Brook being recognized as a 2015 TiE50 Top Start-Up as well as being listed as one of the best ideas from Finovate by WealthManagement.com. An API version of KNEWSAPP is planned for later this year. Minetta Brook will be attending the Rosenblatt Securities 2015 Financial Technologies Summit in New York on Monday, September 28th, 2015.
About Minetta Brook Founded in 2011, Minetta Brook was formed in response to the explosion of unstructured data in our lives. We build software to help users rapidly navigate, discover, and track relevant content from large, dynamic bodies of information.
Our team comprises scientists and technologists who understand information, finance, and business. We developed the trading systems that became the model for every single modern trading system. Our software underpins NASDAQ's messaging infrastructure. We have built algorithms for trading and extracted news for algorithms. We designed the massively scale-able server clusters and information architecture that run systems on Wall Street.
For more information, visit http://www.minettabrook.com