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  • Book Overview & Buying Python for Algorithmic Trading Cookbook
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Python for Algorithmic Trading Cookbook

Python for Algorithmic Trading Cookbook

By : Jason Strimpel
4.3 (20)
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Python for Algorithmic Trading Cookbook

Python for Algorithmic Trading Cookbook

4.3 (20)
By: Jason Strimpel

Overview of this book

Discover how Python has made algorithmic trading accessible to non-professionals with unparalleled expertise and practical insights from Jason Strimpel, founder of PyQuant News and a seasoned professional with global experience in trading and risk management. This book guides you through from the basics of quantitative finance and data acquisition to advanced stages of backtesting and live trading. Detailed recipes will help you leverage the cutting-edge OpenBB SDK to gather freely available data for stocks, options, and futures, and build your own research environment using lightning-fast storage techniques like SQLite, HDF5, and ArcticDB. This book shows you how to use SciPy and statsmodels to identify alpha factors and hedge risk, and construct momentum and mean-reversion factors. You’ll optimize strategy parameters with walk-forward optimization using VectorBT and construct a production-ready backtest using Zipline Reloaded. Implementing all that you’ve learned, you’ll set up and deploy your algorithmic trading strategies in a live trading environment using the Interactive Brokers API, allowing you to stream tick-level data, submit orders, and retrieve portfolio details. By the end of this algorithmic trading book, you'll not only have grasped the essential concepts but also the practical skills needed to implement and execute sophisticated trading strategies using Python.
Table of Contents (16 chapters)
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Technical requirements

This book relies on the Anaconda distribution of Python. We’ll use Jupyter Notebook and Python script files to write the code. Unless specified otherwise, all the code can be written in Jupyter Notebooks.

Download and install the Anaconda distribution of Python. You can do this by going to https://www.anaconda.com/download. Depending on your operating system, the instructions for downloading and installing will vary. Please refer to the Anaconda documentation for detailed instructions.

Anaconda ships with a package manager called conda. Package managers make it easy to install, remove, and update Python packages. There’s a great cheat sheet for the conda package manager that you can download from https://docs.conda.io/projects/conda/en/4.6.0/_downloads/52a95608c49671267e40c689e0bc00ca/conda-cheatsheet.pdf.

Once you’ve installed the Anaconda distribution, open your Terminal on Mac or Linux or the Anaconda Prompt on Windows. If you’re a Windows user, make sure to use the Command Prompt instead of the Powershell prompt. Then follow these steps:

  1. Update the conda package manager:
    conda update -n base conda -y

Quick tip: Enhance your coding experience with the AI Code Explainer and Quick Copy features. Open this book in the next-gen Packt Reader. Click the Copy button (1) to quickly copy code into your coding environment, or click the Explain button (2) to get the AI assistant to explain a block of code to you.

The next-gen Packt Reader is included for free with the purchase of this book. Unlock it by scanning the QR code below or visiting https://www.packtpub.com/unlock/9781835084700.

  1. Create a virtual environment:
    conda create -n my-quant-stack python=3.10 -y
  2. After the installation process is complete, activate the environment:
    conda activate my-quant-stack
  3. Install Jupyter Notebook using the package manager that ships with Python, pip:
    pip install notebook matplotlib

This will set up a virtual environment using Python 3.10 and install Jupyter Notebook.

This chapter will use Two Python libraries to acquire financial market data: the OpenBB Platform and pandas_datareader. The good news is that installing the OpenBB Platform installs many of the libraries you will need to acquire financial market data, including pandas_datareader. As such, there is no need to install the libraries separately.

Install the OpenBB Platform with all extensions and providers (both officially supported and community-maintained ones) using pip:

pip install openbb[all]

This is the easiest way to set up the OpenBB Platform for this book.

Important note

In a macOS zsh Terminal shell, add quotation marks around the library name: "openbb[all]"

To install a single extension:

pip install openbb[charting]
pip install openbb[ta]

Or install a single provider:

pip install openbb[yfinance]

To install the Nightly distribution (this installs all extras by default):

pip install openbb-nightly

Important note

At the time of writing, installing the OpenBB Platform using pip isn’t compatible with environments such as Google Colab and Kaggle since they come with preinstalled packages that can conflict with the ones used with the OpenBB Platform. If you run into trouble installing the OpenBB Platform, please check the online documentation for the most up-to-date instructions.

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