Bloomberg has launched BQuant Enterprise, a public/private-cloud-based analytics platform for quantitative analysts and data scientists in financial markets.
BQuant is the first data science solution from Bloomberg that is designed specifically for financial markets and offers operation-ready access to Bloomberg’s comprehensive range of high-quality, market leading, multi-asset-class financial and alternative data sets.
“The largest global financial firms have fully embraced quantitative investing to improve trading strategies, while reducing expenses,” says Tony McManus, Global Head of Enterprise Data at Bloomberg.
He adds, “However, the high cost of entry has put the majority of firms at a disadvantage. BQuant Enterprise levels the playing field with a high-performance platform that can operate as your core platform or can be integrated in days with firms’ existing data science research environments,”
The financial industry’s leading firms have invested heavily in building systems to support quantitative analysts, who use mathematical models, voluminous data sets, and computational power to evaluate investment strategies and generate new ideas.
BQuant Enterprise offers analysts more efficient workflows for creating, validating, and putting their models in production for decision making.
The platform comprises finance-specific tools, services, and libraries to support a broad range of quantitative analytics, including factor model evaluation, back testing strategies, and analysing portfolios, across asset classes. Features include:
Also on offer are access to Bloomberg’s comprehensive range of multi-asset-class financial and alternative linked data sets as well as to an interactive platform rooted in Python and Jupiter notebooks.
Quantitative analysts and data scientists focused on financial markets typically use Python’s open-source scientific computing ecosystem and empowers advanced users to build their own applications.
The platform also has API-first analytics and domain-specific tools as well as research distribution capabilities. In addition, it is cloud ready and compatible with the most popular public clouds, as well as on-premises private and hybrid cloud environments.
“In building BQuant Enterprise, our goal was to develop an open architecture based on a powerful tech stack that is readily accessible and infinitely extensible, so it can grow as our customers grow,” says Shawn Edwards, Bloomberg’s Chief Technology Officer.
He adds, “Utilising the power of the cloud, we’re giving clients a turnkey environment where they can connect to their existing systems, bring their own data, mix it with Bloomberg’s comprehensive data sets, and enhance the collaboration of their investment professionals as they test and deploy new quantitative investment strategies.”
©Markets Media Europe 2021
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