Discover how to build and backtest algorithmic trading strategies with
Zipline
Key Features:
-
Get to grips with market data and stock analysis and visualize data to
gain quality insights
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Find out how to systematically approach quantitative research and
strategy generation/backtesting in algorithmic trading
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Learn how to navigate the different features in Python's data analysis
libraries
Book Description:
Algorithmic trading helps you stay ahead of the markets by devising
strategies in quantitative analysis to gain profits and cut losses.
The book starts by introducing you to algorithmic trading and explaining
why Python is the best platform for developing trading strategies.
You'll then cover quantitative analysis using Python, and learn how to
build algorithmic trading strategies with Zipline using various market
data sources. Using Zipline as the backtesting library allows access to
complimentary US historical daily market data until 2018. As you
advance, you will gain an in-depth understanding of Python libraries
such as NumPy and pandas for analyzing financial datasets, and explore
Matplotlib, statsmodels, and scikit-learn libraries for advanced
analytics. You'll also focus on time series forecasting, covering
pmdarima and Facebook Prophet.
By the end of this trading book, you will be able to build predictive
trading signals, adopt basic and advanced algorithmic trading
strategies, and perform portfolio optimization.
What You Will Learn:
-
Discover how quantitative analysis works by covering financial
statistics and ARIMA
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Use core Python libraries to perform quantitative research and
strategy development using real datasets
-
Understand how to access financial and economic data in Python
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Implement effective data visualization with Matplotlib
-
Apply scientific computing and data visualization with popular Python
libraries
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Build and deploy backtesting algorithmic trading strategies
Who this book is for:
This book is for data analysts and financial traders who want to explore
how to design algorithmic trading strategies using Python's core
libraries. If you are looking for a practical guide to backtesting
algorithmic trading strategies and building your own strategies, then
this book is for you. Beginner-level working knowledge of Python
programming and statistics will be helpful.
