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Python for Algorithmic Trading Cookbook

You're reading from   Python for Algorithmic Trading Cookbook Recipes for designing, building, and deploying algorithmic trading strategies with Python

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Product type Paperback
Published in Aug 2024
Publisher Packt
ISBN-13 9781835084700
Length 406 pages
Edition 1st Edition
Languages
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Author (1):
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Jason Strimpel Jason Strimpel
Author Profile Icon Jason Strimpel
Jason Strimpel
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Toc

Table of Contents (16) Chapters Close

Preface 1. Chapter 1: Acquire Free Financial Market Data with Cutting-Edge Python Libraries FREE CHAPTER 2. Chapter 2: Analyze and Transform Financial Market Data with pandas 3. Chapter 3: Visualize Financial Market Data with Matplotlib, Seaborn, and Plotly Dash 4. Chapter 4: Store Financial Market Data on Your Computer 5. Chapter 5: Build Alpha Factors for Stock Portfolios 6. Chapter 6: Vector-Based Backtesting with VectorBT 7. Chapter 7: Event-Based Backtesting Factor Portfolios with Zipline Reloaded 8. Chapter 8: Evaluate Factor Risk and Performance with Alphalens Reloaded 9. Chapter 9: Assess Backtest Risk and Performance Metrics with Pyfolio 10. Chapter 10: Set Up the Interactive Brokers Python API 11. Chapter 11: Manage Orders, Positions, and Portfolios with the IB API 12. Chapter 12: Deploy Strategies to a Live Environment 13. Chapter 13: Advanced Recipes for Market Data and Strategy Management 14. Index 15. Other Books You May Enjoy

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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Python for Algorithmic Trading Cookbook
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Python for Algorithmic Trading Cookbook
Published in: Aug 2024
Publisher: Packt
ISBN-13: 9781835084700
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