Automated Trading Development with Python, Installing Zipline

Python is a very popular programming language in the fields of data science, machine learning, and algorithmic trading. In particular, there are various libraries available to implement and test automated trading. Among them, Zipline is a popular backtesting framework for algorithmic trading. In this article, we will take a closer look at how to install and use Zipline.

1. Introduction to Zipline

Zipline is a Python-based open-source algorithmic trading backtesting library for financial markets developed by Quantopian. Zipline provides the following key features:

  • Simulation: You can simulate various strategies to evaluate performance.
  • Data handling: It provides tools to easily handle and analyze financial data.
  • Scalability: Custom indicators and strategies can be easily added.
  • Visualization: It helps visually represent results for better understanding.

2. Preparing to Install Zipline

Before installing Zipline, a few preparations are needed. You can follow the steps below to proceed with the installation.

2.1. System Requirements

Zipline is recommended for installation on Linux and Mac OS. If you want to use it on Windows, it is recommended to use Windows Subsystem for Linux (WSL). Additionally, Python 3.5 or higher is required.

2.2. Setting Up a Virtual Environment

It is advisable to set up a virtual environment to install Zipline. This helps manage dependencies. Here is how to set up a virtual environment:

python -m venv zipline-env
source zipline-env/bin/activate  # Linux / Mac OS
zipline-env\Scripts\activate  # Windows

3. Installing Zipline

The next step is to install Zipline. Zipline can be installed via pip. The installation command is as follows:

pip install zipline

3.1. Installing Required Packages

Installing Zipline requires several essential packages, such as numpy and pandas. You can install them as follows:

pip install numpy pandas matplotlib pytz

3.2. In Case of Problems

There may be issues during installation. In this case, use the command below to install Zipline:

pip install git+https://github.com/quantopian/zipline.zip

4. Validating Zipline

Once Zipline is installed, you can check whether the installation was successful by using the code below.

import zipline
print(zipline.__version__)

If you run the above code and no errors occur, then Zipline is installed successfully. If it runs normally, you will be able to check the version of Zipline.

5. Trying Out Zipline

Now that Zipline is installed, let’s create a basic automated trading strategy.

5.1. Loading Basic Data

The way to load data in Zipline is as follows:

from zipline.api import order, record, symbol
from zipline import run_algorithm
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

def initialize(context):
    context.asset = symbol('AAPL')
    
def handle_data(context, data):
    order(context.asset, 1)  # Buy AAPL stock
    record(AAPL=data.current(context.asset, 'price'))

start = pd.Timestamp('2020-01-01', tz='utc')
end = pd.Timestamp('2020-01-31', tz='utc')

run_algorithm(start=start, end=end, initialize=initialize, handle_data=handle_data)  # Run algorithm

The code above is an example of writing and executing a simple strategy that buys AAPL (Apple Inc.) stock. It is very useful for understanding the basic structure.

5.2. Visualizing Results

Zipline can visualize results using matplotlib. You can add the following code to visualize:

results = run_algorithm(start, end, initialize=initialize, handle_data=handle_data)
results.portfolio_value.plot()
plt.show()

This code visualizes the portfolio value during January 2020. It allows you to see the performance of the algorithm strategy at a glance.

6. Conclusion

Zipline is a powerful tool for algorithmic trading using Python. Through the contents explained in this article, you learned how to install Zipline and implement a basic trading strategy. By taking this step, you can gain confidence in developing and backtesting more complex strategies.

7. Next Steps

Now that you have installed Zipline and learned the basics, consider the following topics for your next steps:

  • Implementing advanced strategies
  • Integrating data sources
  • Risk management and portfolio optimization
  • Evaluating and analyzing strategy performance

If you need more resources and documentation, refer to the official Zipline documentation.

We encourage you on your journey to enhance your understanding of technical trading and grow into a successful investor!