Dr Jessica Stauth: Portfolio and Risk Analytics in Python with pyfolio | PyData NYC 2015

Dr Jessica Stauth: Portfolio and Risk Analytics in Python with pyfolio PyData NYC 2015 Pyfolio is a recent open source library developed by Quantopian to support common financial analyses and plots of portfolio allocations over time. Pyfolio is a tear sheet that consists of various individual plots that provide a comprehensive image of the performance of a trading algorithm and features advanced statistical analyses using Bayesian modeling. (http://quantopian.github.io/pyfolio/). Python is quickly establishing itself as the lingua franca for quantitative finance. The rich stack of open source tools like Pandas, the Jupyter notebook, and Seaborn, provide quants with a rich and powerful tool belt to analyze financial data. While useful for Quantitative Finance, these general purpose libraries lack support for common financial analyses like the computation of certain risk factors (Sharpe, Fama-French), or plots of portfolio allocations over time. Pyfolio is a recent open source tool developed by Quantopian to fill this gap. At the core of pyfolio is a so-called tear sheet that consists of various individual plots that provide a comprehensive image of the performance of a trading algorithm/portfolio. In addition, the library features advanced statistical analyses using Bayesian modeling. The software can be used stand-alone, w**ith our open-source backtesting library Zipline and is available on the Quantopian platform. This talk will be a tutorial on how to get the most out of this library (http://quantopian.github.io/pyfolio/). Slides available here: http://www.slideshare.net/JessStauth/pydata-nyc-2015 Relevant GitHub repos: https://github.com/quantopian/pyfolio https://github.com/quantopian/zipline www.pydata.org 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. Want to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps