Accelerate your Backtesting with Zipline Reloaded by TEJ

Accelerate your Backtesting with Zipline Reloaded by TEJ

Backtesting is a crucial step in developing effective trading strategies. It allows traders to evaluate the performance of their strategies using historical market data. However, conducting backtests can be time-consuming and challenging without the right tools. That’s where Zipline Reloaded, modified by TEJ, comes in.

Zipline is a powerful open-source Python library for simulating and backtesting trading strategies. With its user-friendly interface and extensive functionality, it has become a popular choice among traders and researchers. TEJ has taken Zipline to the next level by enhancing its features and incorporating valuable data from their industry-leading financial database.

Installation

To get started with Zipline Reloaded, make sure you have Python 3.8 or above installed on your system. Zipline also requires other Python packages such as Pandas, Numpy, Logbook, and Exchange-calendars. We recommend using Anaconda as your development environment, as it makes package management seamless.

To install Zipline Reloaded, follow these steps:

1. Download the zipline-tej.yml file from the zipline-tej.yml link for Windows or zipline-tej_mac.yml for macOS.
2. Open an Anaconda prompt and navigate to the folder where the downloaded file is located.
3. Create a virtual environment and activate it using the following commands:

#
Windows Users
$ conda env create -f zipline-tej.yml
$ conda activate zipline-tej

#
Mac Users
$ conda env create -f zipline-tej_mac.yml
$ conda activate zipline-tej

Alternatively, if you prefer to create a virtual environment manually, you can use the command below:

#
$ conda create -n  python=3.10
$ conda activate 
$ pip install zipline-tej

For Docker users, TEJ provides a consistent and stable environment on Docker hub. You can follow the instructions provided to download and use the Docker image.

Quick Start

To demonstrate the capabilities of Zipline Reloaded, let’s walk through a simple buy-and-hold trading algorithm implemented using the Zipline CLI.

#python
from zipline.api import order, record, symbol

def initialize(context):
    context.asset = symbol("2330")
    
def handle_data(context, data):
    order(context.asset, 10)
    record(TSMC=data.current(context.asset, "price"))
    
def analyze(context=None, results=None):
    import matplotlib.pyplot as plt

    # Plot the portfolio and asset data.
    ax1 = plt.subplot(211)
    results.portfolio_value.plot(ax=ax1)
    ax1.set_ylabel("Portfolio value (TWD)")
    ax2 = plt.subplot(212, sharex=ax1)
    results.TSMC.plot(ax=ax2)
    ax2.set_ylabel("TSMC price (TWD)")

    # Show the plot.
    plt.gcf().set_size_inches(18, 8)
    plt.show()

To run this algorithm using the Zipline CLI, you’ll need to download some market data with historical prices and trading volumes. Set the necessary environment variables by following the instructions provided in the README.

After setting the environment variables, you can ingest the data and run the backtesting algorithm using the following commands:

#
$ zipline ingest -b tquant
$ zipline run -f buy_and_hold.py --start 20200101 --end 20220101 -o bah.pickle --no-benchmark --no-treasury

The resulting performance DataFrame will be saved as bah.pickle, which you can load and analyze from Python or any other tool of your choice.

Enhance your backtesting strategy with Jupyter Notebook

Zipline Reloaded also provides integration with Jupyter Notebook, allowing you to leverage its interactive features while developing and analyzing your trading strategies. To get started with Jupyter Notebook and Zipline, follow these steps:

1. Open an Anaconda prompt and activate the zipline-tej environment.
2. Start Jupyter Notebook by running the command jupyter notebook.
3. Create a new notebook and select the Python [conda env:zipline-tej] kernel.

From there, you can write and execute your Zipline algorithms directly in Jupyter Notebook. Make sure to set the necessary environment variables before running your code.

Deep Dive into Zipline Reloaded

Zipline Reloaded offers a wide range of features and capabilities beyond what we’ve covered in this brief overview. Here are some additional resources where you can explore and learn more about this powerful tool:

• Zipline Tutorials: TEJ provides a collection of tutorials that cover various aspects of using Zipline Reloaded, complete with example code and explanations.

Conclusion

Zipline Reloaded, modified by TEJ, is a game-changer for backtesting trading strategies. Its enhanced features, integration with TEJ’s financial database, and seamless integration with popular tools like Jupyter Notebook make it a must-have for any serious trader or researcher.

Whether you’re a seasoned trader looking to fine-tune your trading strategies or a beginner exploring the world of algorithmic trading, Zipline Reloaded has everything you need to accelerate your backtesting process and gain a competitive edge in the markets.

So don’t wait, start exploring the possibilities of Zipline Reloaded today and take your trading strategies to the next level!

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*For more information and to get started with Zipline Reloaded, visit the Zipline TEJ GitHub repository.