Gus Gordon is a Data Engineer at Quantopian, an algorithmic investing platform and hedge fund manager. He works on the research team, developing tools for analyzing financial data and evaluating the performance of trading strategies. Gus studied physics and economics at Bucknell University.
In this talk, Gus will go through a clean example of how to design a financial trading strategy using open source Python tools. We’ll start off by analyzing a raw trading signal in alphalens, then transition that signal into an algorithm that we can backtest with zipline. Finally, we’ll review the results of the backtest by going through some plots generated by pyfolio.
PyData Ann Arbor is a group for amateurs, academics, and professionals currently exploring various data ecosystems. Specifically, we seek to engage with others around analysis, visualization, and management. We are primarily focused on how Python data tools can be used in innovative ways but also maintain a healthy interest in leveraging tools based in other languages such as R, Java/Scala, Rust, and Julia.
PyData Ann Arbor strives to be a welcoming and fully inclusive group and we observe the PyData Code of Conduct. PyData is organized by NumFOCUS.org, a 501(c)3 non-profit in the United States.
“use what you have learned to make something better and share with others”