Recently, the US SEC published a proposal for how to address the current lack of transparency of asset-backed securities through changing disclosure requirements to include the provision of a Python computer program. The goal is to capture all the complicated terms of the deal in code that can be used to analyze the cash flows in each deal and how the returns will get split up between different parties. Currently, investors, fund managers, and investment managers receive a complex, textual description of this information in the prospectus, which makes it difficult for them to perform or visualize a rigorous quantitative or if-then analysis of the asset-backed securities.
This all begs the question “Why Python?” One of the answers is that it’s open source and while there are a number of proprietary financial modeling solutions and more than a few trade description languages in use on Wall Street – there is little use asking for openness and transparency from issuers if the interpreter for that code is proprietary in nature. That said, Python has other aspects that make it a good choice for these purposes and has been widely used on Wall Street and in the finance community for financial modeling and number crunching.
At the very least, it’s not enough to have open data, one has to have open tools to fulfill the transparency requirements to establish meaningful use of financial information. Buyers, Sellers and Regulators alike need an open technology means to accurately and efficiently interpret financial information.
This presentation will discuss some of the aspects of Python that make it a good fit for the SEC’s proposal and some of the challenges and the implications of using Python for financial analysis. This presentation will also discuss some opportunities for collaboration between regulators and the open source related to the development of an ecosystem of open source projects that can exploit the availability of this proposed new rich source of financial information.
Sponsored by ActiveState
Diane Mueller is Director, Enterprise Product Management at ActiveState. She has been designing and implementing products and applications embedded into mission critical financial and accounting systems at F500 corporations for over 20 years. Diane has been actively involved in development efforts of XBRL Open Standard for the past 11 years. She serves on both the XBRL International Steering Committee and the Best Practices Board, chairing the software interoperability working group and the XBRL Rendering Technical Working Group, as well as an active member of the RIXML.org working group.
In addition, she is the host and editor of XBRLSpy.com and a half dozen other drupal-based sites that allow her to pontificate on her interests ranging from geocaching, her pugs, and the Pacific Northwest she calls home.
Trent is ActiveState’s Senior Python developer and ActiveState’s Komodo lead. As a core Python contributor, Trent was involved in specifying Python’s logging package and in transitioning Python to 64-bit architectures. Trent is also the author of a number of Python modules including cmdln, go, python-markdown2. As the Komodo lead, Trent also works on numerous OpenKomodo projects.
Trent has been a member of the Python Software Foundation since its inception. He regularly attends and hosts Python industry events and meetings, most recently PyCon and VanPyZ, and writes a blog about Python development .
Trent was a software developer at EA before joining ActiveState in 2000. He earned both a Bachelor of Engineering and a B. Sc. in Computer Science Degree from the University of Saskatchewan.
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