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Screenshot of a breaking news alert e-mail from Q2 2017
Axioma, a provider of investment risk and portfolio management solutions, has launched the Axioma Portfolio Optimizer Python API (application program interface). The API, built on Axioma’s new Optimization Web Services, enables users to leverage the features of Axioma’s best-in-class Portfolio Optimizer using Python.
Python is fast becoming the language of choice for quants who use it to prepare alpha models and other typical inputs into the optimization process,” said Pam Vance, Managing Director, Applications Development at Axioma. “We built the Optimizer API in Python because of the ease of integration with our clients’ proprietary model-production processes.
Both the Web Services and the Python API enable clients to access Axioma’s full library of strategy-building options for portfolio construction. They use the same Second-Order Cone Programming (SOCP) optimization engine as Axioma’s C++ and Java APIs.
Financial institutions’ widespread adoption of Web Services drives consistency and efficiency in the flow of data and insight across the organization. This results in greater collaboration and fewer organizational silos,“ Vance added.
Clients can now share optimization use-cases enterprise-wide using the underlying Web Services repository, which makes it easier for teams to add inputs and share analyses. The repository maintains live cases that are instantly accessible and archived.
The Python API and the Optimizer Web Services are completely open to content from any source, be it from Axioma, a third party, or clients’ internal research teams. As a result, clients can apply proprietary return, risk and transaction cost models that are created in Python, to customize their portfolio optimization analyses.
Another extensive feature of this interface is its ability to incorporate ETFs, futures and other composite instruments with a full look-through to their individual constituents. Users can either use Axioma’s integrated content or create their own custom compositions to take full advantage of the look-through to monitor and control the risk exposures of their portfolios.