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)

Volatility indicators – Bollinger Bands

Bollinger Bands are a lagging volatility indicator. Bollinger Bands consist of three lines, or bands—the middle band, the lower band, and the upper band. The gap between the bands widens when the price volatility is high and reduces when the price volatility is low.

Bollinger Bands are an indicator of overbought or oversold conditions. When the price is near the upper band or the lower band, this indicator predicts that a reversal will happen soon. The middle band acts as a support or resistance level.

The upper band and lower band can also be interpreted as price targets. When the price bounces off of the upper band and crosses the middle band, the lower band becomes the price target, and vice versa.

The formulae for computing the Bollinger Bands are as follows.

Bollinger Bands define the typical price (TP) as the average of the high, low, and close of a candle. The TP is used for computing the middle band, lower band, and upper...