You're reading from Hands-On Financial Trading with Python A practical guide to using Zipline and other Python libraries for backtesting trading strategies

Product type Paperback

Published in Apr 2021

Publisher Packt

ISBN-13 9781838982881

Length 360 pages

Edition 1st Edition

Languages

Python

Tools

NumPy

Concepts

Data Analysis

Authors (2):

Sourav Ghosh

Jiri Pik

View More author details

Table of Contents (15) Chapters

Preface

1. Section 1: Introduction to Algorithmic Trading

2. Chapter 1: Introduction to Algorithmic Trading FREE CHAPTER

3. Section 2: In-Depth Look at Python Libraries for the Analysis of Financial Datasets

4. Chapter 2: Exploratory Data Analysis in Python

5. Chapter 3: High-Speed Scientific Computing Using NumPy

6. Chapter 4: Data Manipulation and Analysis with pandas

7. Chapter 5: Data Visualization Using Matplotlib

8. Chapter 6: Statistical Estimation, Inference, and Prediction

9. Section 3: Algorithmic Trading in Python

10. Chapter 7: Financial Market Data Access in Python

11. Chapter 8: Introduction to Zipline and PyFolio

12. Chapter 9: Fundamental Algorithmic Trading Strategies

13. Other Books You May Enjoy

Appendix A: How to Setup a Python Environment

Structuring Zipline/PyFolio backtesting modules

Typical Zipline backtesting code defines three functions:

initialize: This method is called before any simulated trading happens; it's used to enrich the context object with the definition of tickers and other key trading information. It also enables commission and slippage considerations.
handle_data: This method downloads the market data, calculates the trading signals, and places the trades. This is where you put the actual trading logic on entry/exit positions.
analyze: This method is called to perform trading analytics. In our code, we will use pyfolio's standard analytics. Notice that the pf.utils.extract_rets_pos_txn_from_zipline(perf) function returns any returns, positions, and transactions for custom analytics.

Finally, the code defines the start date and the end date and performs backtesting by calling the run_algorithm method. This method returns a comprehensive summary of all the trades to...