FactSet and Quantopian to launch data analysis platform

Source: FactSet

FactSet, a global provider of integrated financial information, analytical applications, and industry-leading services, and Quantopian, a crowd-sourced asset manager and creator of the open-source quantitative finance platform, today announced a new strategic relationship and a plan to launch a pioneering data analysis solution called Quantopian Enterprise that allows quantitative financial analysts to research and test their investment strategies faster and more effectively.

Quantopian Enterprise combines Quantopian’s industry-leading technology and data from the Open:FactSet Marketplace, allowing clients to simulate how investment algorithms will perform in the real world. Investment professionals will have immediate access to a ready-built research and testing environment, reducing the ramp-up time experienced with traditional platforms. They will also gain access to the financial data, computing resources, and flexible tools they need to create and improve their investment strategies.

“New data sources are growing rapidly, but the tools needed to capitalize on them are not coming to market at the same pace,” said Rich Newman, SVP and Global Head of Content and Technology Solutions, FactSet. “Our work with Quantopian will give clients a powerful platform that addresses the need for better quantitative resources. Access to data alone is simply not enough.”

"With Quantopian Enterprise, quants now have the opportunity to research, craft, and test their investment strategies with even more speed and flexibility," said John Fawcett, Founder and CEO of Quantopian. “We are providing them with the tools, the data, and the environment they need to help reshape how data is used in the investment industry."

FactSet’s alliance with Quantopian follows the successful launch of the Open:FactSet Marketplace and continues the company’s expansion into open data solutions. It will also benefit Quantopian’s 195,000 community members who will have access to FactSet's pre-integrated data in the Python-based research environment in order to explore hypotheses, evaluate factors, and backtest strategies.
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