#### 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.

# Volatility indicators – average true range

Average true range (ATR) is a lagging volatility indicator. ATR is a measure of volatility. High ATR values indicate high volatility, and low values indicate low volatility.

The formula for computing ATR is not straightforward and is hence not mentioned here. If you are interested in the underlying math, please refer to the official documentation of TA-Lib on ATR at http://www.tadoc.org/indicator/ATR.htm. Although it is a good idea to know the mathematics of how this works, this recipe does not require you to understand or remember the given formula. We use a third-party Python package, talib, which provides a ready function for calculating ATR.

## Getting started

Make sure your Python namespace has the following objects:

1. talib (package)
2. pd (module)
3. plot_candlesticks_chart (function)
4. PlotType (enum)
5. historical_data (a pandas DataFrame)

Refer to the Technical requirements section of this chapter to set up these objects.