Visualizing Strategy Metrics - Zipline Tutorial local backtesting and finance with Python p.2

TL;DR

This video is the second part of a tutorial series on using Zipline for backtesting and finance, focusing on reading data and visualizing performance.

Transcript

what's going on everybody and welcome to the second part of the zipline local tutorial miniseries for back testing and doing Finance with Pawnee thon in last tutorial what we did was we just went through the arduous process of getting zipline running on our machine running through a simple just by Apple strategy and we got to this point where we ra... Read More

Key Insights

• 🫠 Zipline allows for reading data from pickle files using the pandas library.
• ❓ Visualization of performance in Zipline can be done by plotting the portfolio value or using the analyze function.
• 🪈 Zipline does not have a limit on the number of variables that can be recorded and plotted.
• 🐼 Custom calculations and visualizations can be performed on the data frame using pandas in Zipline.

Questions & Answers

Q: How can we read data from a pickle file using the pandas library?

To read data from a pickle file, you can use the "read_pickle" function from the pandas library. For example, you can use the code "pd.read_pickle('strat.pickle')" to read the data into a DataFrame.

Q: What is the purpose of the analyze function in Zipline?

The analyze function in Zipline is a built-in function that allows you to perform additional analysis or create custom visualizations. Anything you put in the analyze function will be executed at the end of the backtesting process.

Q: Can we record and plot more than five variables in Zipline?

Unlike quanto peon, Zipline does not have a limit on the number of variables you can record and plot. You can record and plot as many variables as you need for your analysis.

Q: What are some other ways to visualize performance in Zipline?

Besides plotting the portfolio value, you can create custom calculations on the data frame, such as comparing the algorithm period return to the benchmark period return. Additionally, you can use the analyze function to perform various visualizations or activities with your backtesting results.

Summary & Key Takeaways

• The video continues the tutorial on using Zipline for backtesting and finance with Pawnee and focuses on reading data and visualizing performance.

• The presenter demonstrates how to read data from a pickle file using the pandas library and plot the portfolio value.

• Different methods of visualization, including using the analyze function, are discussed.

• The video ends with a preview of upcoming tutorials on bringing in custom data and using it for custom markets.