Python Algorithmic Trading Cookbook

Build a solid foundation in algorithmic trading by developing, testing and executing powerful trading strategies with real market data using Python

Key Features

• Build a strong foundation in algorithmic trading by becoming well-versed with the basics of financial markets
• Demystify jargon related to understanding and placing multiple types of trading orders
• Devise trading strategies and increase your odds of making a profit in stock markets without human intervention

Book Description

Python is a very popular language used to build and execute algorithmic trading strategies. If you want to find out how you can build a solid foundation in algorithmic trading using the language, this cookbook is here to help.

Starting by setting up the Python environment for trading and connectivity with brokers, you'll then learn the important aspects of financial markets. As you progress through this algorithmic trading book, you'll learn to fetch financial instruments, query and calculate various types of candles and historical data, and finally, compute and plot technical indicators. Next, you'll discover how to place various types of orders, such as regular, bracket, and cover orders, and understand their state transitions. You'll also uncover challenges faced while devising and executing powerful algorithmic trading strategies from scratch. Later chapters will take you through backtesting, paper trading, and finally real trading for the algorithmic strategies that you've created from the ground up. You'll even understand how to automate trading and find the right strategy for making effective decisions that would otherwise be impossible for human traders.

By the end of this book, you'll be able to use Python for algorithmic trading by implementing Python libraries to conduct key tasks in the algorithmic trading ecosystem.

What you will learn

• Use Python to set up connectivity with brokers
• Handle and manipulate time series data using Python
• Fetch a list of exchanges, segments, financial instruments, and historical data to interact with the real market
• Understand, fetch, and calculate various types of candles and use them to compute and plot diverse types of technical indicators
• Develop and improve the performance of algorithmic trading strategies
• Perform backtesting and paper trading on algorithmic trading strategies
• Implement real trading in the live hours of stock markets

Who this book is for

If you are a financial analyst, financial trader, data analyst, algorithmic trader, trading enthusiast or anyone who wants to learn algorithmic trading with Python and important techniques to address challenges faced in the finance domain, this book is for you. Basic working knowledge of the Python programming language is expected. Although fundamental knowledge of trade-related terminologies will be helpful, it is not mandatory.

Table of Contents

1. Handling and Manipulating Date, Time, and Time Series Data
2. Stock Markets - Primer on Trading
3. Fetching Financial Data
4. Computing Candlesticks and Historical Data
5. Computing and Plotting of Technical Indicators
6. Placing Trading Orders on the Exchange
7. Placing Bracket and Cover Orders on the Exchange
8. Algorithmic Trading Strategies - Code Step-by-Step
9. Algorithmic Trading - Backtesting
10. Algorithmic Trading - Paper Trading
11. Algorithmic Trading - Real Trading
12. Appendix I
13. Appendix II
14. Appendix III

Pushpak Dagade is working in the area of algorithmic trading with Python for more than 3 years. He is a co-founder and CEO of AlgoBulls, an algorithmic trading platform.