Book Image

Python Algorithmic Trading Cookbook

By : Pushpak Dagade
Book Image

Python Algorithmic Trading Cookbook

By: Pushpak Dagade

Overview of this book

If you want to find out how you can build a solid foundation in algorithmic trading using Python, 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, 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 learn how to place various types of orders, such as regular, bracket, and cover orders, and understand their state transitions. Later chapters will cover backtesting, paper trading, and finally real trading for the algorithmic strategies that you've created. 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 libraries to conduct key tasks in the algorithmic trading ecosystem. Note: For demonstration, we're using Zerodha, an Indian Stock Market broker. If you're not an Indian resident, you won't be able to use Zerodha and therefore will not be able to test the examples directly. However, you can take inspiration from the book and apply the concepts across your preferred stock market broker of choice.
Table of Contents (16 chapters)
Stock Markets - Primer on Trading

When building algorithmic trading systems, it is essential to have an account open with a modern broker that provides APIs for placing and querying trades programmatically. This allows us to control the broking account, which is conventionally operated manually using the broker's website, using our Python script, which would be part of our larger algorithmic trading system. This chapter demonstrates various essential recipes that introduce the essential broker API calls needed for developing a complete algorithmic trading system.

This chapter covers the following recipes:

  • Setting up Python connectivity with the broker
  • Querying a list of instruments
  • Fetching an instrument
  • Querying a list of exchanges
  • Querying a list of segments
  • Knowing other attributes supported by the broker
  • Placing a simple REGULAR order
  • Placing a simple BRACKET order
  • Placing a simple DELIVERY order
  • Placing a simple INTRADAY order
  • Querying margins and funds
  • Calculating the brokerage charged
  • Calculating the government taxes charged

Let's get started!