CloudQuant has added RavenPack analytics to its 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 visualise 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,” says 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,” says Amando Gonzalez, CEO of RavenPack. “We strongly support initiatives designed to give data scientists the tools that liberate ideas to improve financial modelling.”