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Hands-On Financial Trading with Python : A Practical Guide to Using Zipline and Other Python Libraries for Backtesting Trading Strategies by Sourav Ghosh and Jiri Pik (2021, Trade Paperback)

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Hands-On Financial Trading with Python: A practical guide to using Zipline and other Python libraries for backtesting trading strategies, ISBN 1838982884, ISBN-13 9781838982881, Brand New, Free shipping in the US

About this product

Product Identifiers

PublisherPackt Publishing, The Limited

ISBN-101838982884

ISBN-139781838982881

eBay Product ID (ePID)2321146455

Product Key Features

Number of Pages360 Pages

Publication NameHands-On Financial Trading with Python : A Practical Guide to Using Zipline and Other Python Libraries for Backtesting Trading Strategies

LanguageEnglish

SubjectMathematical & Statistical Software, Data Visualization, General

Publication Year2021

TypeTextbook

Subject AreaComputers

AuthorSourav Ghosh, Jiri Pik

FormatTrade Paperback

Dimensions

Item Length3.6 in

Item Width3 in

Additional Product Features

Intended AudienceTrade

Table Of ContentTable of Contents Introduction to algorithmic trading Exploratory Data Analysis in Python High-speed Scientific Computing using NumPy Data Manipulation and Analysis with Pandas Data Visualization using Matplotlib Statistical Estimation, Inference, and Prediction Financial Market Data Access in Python Introduction to Zipline and PyFolio Fundamental algorithmic trading strategies

SynopsisBuild and backtest your algorithmic trading strategies to gain a true advantage in the market Key Features 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 Book 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. 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 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., 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 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 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 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., This book focuses on key Python analytics and algorithmic trading libraries used for backtesting. With the help of practical examples, you will learn the principle aspects of trading strategy development. The 14 profitable strategies included in the book will also help you build intuitions that will enable you to create your own strategy.