November 20, 2018
CloudQuant LLC today announced the addition of RavenPack analytics within their trading strategy incubator. Crowd researchers can now use RavenPack historical data to discover tradable alpha signals on CloudQuant’s online Python and JupyterLab-based tools.
RavenPack is a leading provider of big data analytics for financial services that enables hedge funds, banks and asset managers to query and visualize unstructured data including insights from thousands of news and social media sources.
“We are thrilled to include RavenPack analytics in our ecosystem as they have become a vital source of alpha for quantitative investors,” said Morgan Slade, CEO of CloudQuant. “Our community is already finding promising signals that originate from the very popular RavenPack datasets.”
Crowd-based research tools are increasing in popularity along with the rapidly growing data science field. RavenPack and Cloudquant are finding that crowd researchers desire access to Wall Street professional-quality tools and datasets, which enable them to thrive in the professional investment field.
“We were impressed with how CloudQuant provides anyone with Python-coding skills the opportunity to mine our datasets for alpha signals and earn compensation for their contributions,” said Amando Gonzalez, CEO of RavenPack. “We strongly support initiatives designed to give data scientists the tools that liberate ideas to improve financial modeling.”
CloudQuant is the cloud-based trading strategy incubator. Quantitative analysts around the world create and test trading strategies leveraging free institutional grade technology. By providing the capital, technology, and trading acumen to develop and utilize trading strategies, CloudQuant offers a mutually beneficial profit sharing agreement enabling both parties to profit.
CloudQuant LLC, who officially launched in 2017, is a wholly owned subsidiary of Kershner Trading Group LLC.
RavenPack is the leading provider of big data analytics for the financial services industry. Financial professionals rely on RavenPack for its speed and accuracy in analyzing large analyzing large amounts of unstructured content. The company’s products allow clients to enhance returns, reduce risk and increase efficiency by systematically incorporating the effects of public information in their models or workflows.
RavenPack Company Page
+34 952 90 73 90
Please use your business email. If you don't have one, please email us at email@example.com.
By providing your personal information and submitting your details, you acknowledge that you have read, understood, and agreed to our Privacy Statement and you accept our Terms and Conditions. We will handle your personal information in compliance with our Privacy Statement. You can exercise your rights of access, rectification, erasure, restriction of processing, data portability, and objection by emailing us at firstname.lastname@example.org in accordance with the GDPRs. You also are agreeing to receive occasional updates and communications from RavenPack about resources, events, products, or services that may be of interest to you.
Your request has been recorded and a team member will be in touch soon.