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Key benefits

Get quality insights from market data, stock analysis, and create your own data visualisations

Learn how to navigate the different features in Python’s data analysis libraries

Start systematically approaching quantitative research and strategy generation/backtesting in algorithmic trading

Description

Creating an effective system to automate your trading can help you achieve two of every trader’s key goals; saving time and making money. But to devise a system that will work for you, you need guidance to show you the ropes around building a system and monitoring its performance. This is where Hands-on Financial Trading with Python can give you the advantage. This practical Python book will introduce you to Python and tell you exactly why it’s 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. As you progress, you’ll pick up lots of skills like 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 to help you get —and stay—ahead of the markets.

Who is this book for?

If you’re a financial trader or a data analyst who wants a hands-on introduction to designing algorithmic trading strategies, then this book is for you. You don’t have to be a fully-fledged programmer to dive into this book, but knowing how to use Python’s core libraries and a solid grasp on statistics will help you get the most out of this book.

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

What do you get with eBook?

Instant access to your Digital eBook purchase

Download this book in EPUB and PDF formats

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

AI Assistant (beta) to help accelerate your learning

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Amazon verified reviews

richieloco Feb 07, 2024

I expected more about financial trading with python but large parts are about data analysis, manipulation, visualisation... Only the final section is on algorithmic trading.

Amazon Verified review

No Quarter Sep 01, 2023

Got this book in a python book bundle and thought that it would be a decent starting point to use python to start planning trades. Going through the book, this is for people that have a fairly broad knowledge of python, not just a basic working knowledge, since a lot of the chapters in this book are out of date. The first 2 parts new users can kind of get through if they put in the work, but part 3 requires a lot of knowledge since the modules are out of date/not updated.The book also does a bad job of actually explaining anything. The code is given and pictures showing what the code, as typed, should produce. There is no explanation of any of the values in any of the code that is giving. The book also does not really explain any of the results that you get, such as what you should do with any of the data. This leads me to be very confused about who this book is for. Programmers will know where to get all of the information in this book and none of the programming is that complex, but might not understand why having some of the graphs are important or what information is important from the information that is taught to scrape/get with an api. Traders/financial analysts will understand most of the charts and what to do with the data, but will struggle getting through the coding in this book and understanding what can be changed to fit their needs.The best part of this book is probably Chapter 6 and 7, since most of the code works and this is where the book tells you what APIs to look for (NASDAQ LINK/quandl in the book, IEXCloud, YahooFinance module, marketstats and that is about it).

Andrew Combs Dec 30, 2021

Like the other reviewer has said, the packages are out of date already and it is a massive pain to get them all working together. Pick another book unless you are prepared for many hours of getting the software configured.

aditya Karampudi Aug 24, 2021

I was initially skeptical about the contents of this one, but after going through few chapters, I got the overall structure of the book. It is a latest version that uses zipline and also FB time series library. I have enjoyed it and requires quite some understanding of statistics, regression for better utilization of the book. Overall, it is a great book for trading and definitely worth a try!

Amazon Customer Aug 23, 2021

Hands-on Financial Trading with Python is one of the best algorithmic trading books I’ve read. For those of you who want to get into the realm of Algo trading, you should not skip a single chapter of this book. As I am reading the book, I especially enjoy chapter 3, 4, and 5 where an in-depth elaboration of NumPy, Pandas and Matplotlib Python libraries are presented with comprehensive and comprehensible hands-on codes with which I could follow long. However, chapter 6 does require some statistical background to be able to comprehend the time series models generated by FB’s Prophet library. Besides, I want to give the author a big shout-out to the zipline chapter. It was a pain for me to install and be able to code in a zipline environment when I just got started, and there weren’t many reliable resources on how to install zipline properly across different operating systems, as well as how to create custom data bundle, which this book provides. Therefore, you should not miss this book if you plan on getting started with zipline, as it will save you a lot of time.Moreover, I want to give the author a suggestion: if you could provide another chapter introducing the latest variant of zipline, i.e. zipline-trader, in terms of its new features, how to install it on Mac OS, as well as how to live-trade with it, this book will definitely be more informative to the intermediate and even advanced Algo traders.

Hands-On Financial Trading with Python: A practical guide to using Zipline and other Python libraries for backtesting trading strategies

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