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A Data Science Approach to Systemic Risk - Nikolai Nowaczyk
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PyData London 2018
We present data science approach to evaluate, predict and optimize financial regulation. As the trade data of the real financial system is proprietary, we use random graph generation to produce a dataset of simulated financial systems and study the impact of prominent regulations like Initial Margin over time. This uses various open source technologies in Python and C++.
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PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.
PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases. 00:00 Welcome!
00:10 Help us add time stamps or captions to this video! See the description for details.
We present data science approach to evaluate, predict and optimize financial regulation. As the trade data of the real financial system is proprietary, we use random graph generation to produce a dataset of simulated financial systems and study the impact of prominent regulations like Initial Margin over time. This uses various open source technologies in Python and C++.
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PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.
PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases. 00:00 Welcome!
00:10 Help us add time stamps or captions to this video! See the description for details.
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