Measuring backtest performance with pyfolio

Pyfolio facilitates the analysis of portfolio performance, both in and out of sample using a rich set of metrics and visualizations. It produces tear sheets that cover the analysis of returns, positions, and transactions, as well as event risk during periods of market stress using several built-in scenarios. It also includes Bayesian out-of-sample performance analysis.

Pyfolio relies on portfolio returns and position data and can also take into account the transaction costs and slippage losses of trading activity. It uses the empyrical library, which can also be used on a standalone basis to compute performance metrics.

Creating the returns and benchmark inputs

The library is part of the Quantopian ecosystem and is compatible with Zipline and Alphalens. We will first demonstrate how to generate the requisite inputs from Alphalens and then show how to extract them from a Zipline backtest performance DataFrame. The code...