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Hands-On Financial Trading with Python - A practical guide to using Zipline and other Python libraries for backtesting trading strategies (Paperback)
Loot Price: R1,251
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Hands-On Financial Trading with Python - A practical guide to using Zipline and other Python libraries for backtesting trading strategies (Paperback)
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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 Find out how
to systematically approach quantitative research and strategy
generation/backtesting in algorithmic trading Learn how to navigate
the different features in Python's data analysis libraries Book
DescriptionAlgorithmic 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 Use core
Python libraries to perform quantitative research and strategy
development using real datasets Understand how to access financial
and economic data in Python Implement effective data visualization
with Matplotlib Apply scientific computing and data visualization
with popular Python libraries Build and deploy backtesting
algorithmic trading strategies Who this book is forThis 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.
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