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)

Fetching historical data using the Renko candlestick pattern

The historical data of a financial instrument can be analyzed in the form of the Renko candlestick pattern, a candlestick pattern that focuses on price movement. This differs from the Japanese candlestick pattern, which focuses on time movement. Brokers typically do not provide historical data as the Renko candlestick pattern via APIs. Brokers usually provide historical data by using the Japanese candlestick pattern, which needs to be converted into the Renko candlestick pattern. A shorter candle interval hints at a localized price movement trend, while a larger candle interval indicates an overall price movement trend. Depending on your algorithmic trading strategy, you may need the candle interval to be small or large. A candle interval of 1 minute is often the smallest available candle interval.

The Renko candlestick pattern works as follows:

  1. Each candle only has open and close attributes.
  2. You define a Brick Count (b) setting...