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)

Developing and improving strategies

In this appendix, we will cover a number of key points regarding algorithmic trading strategies that ought to be considered while executing them.

Strategy profitability is subject to seasons

Strategies may not return good results all year round. They can be seasonal, meaning they may perform well at certain times of the year and not so well at other times. So, it is essential to identify the right time or the right season for a strategy and to use it only at those times.

Strategy profitability is subject to its parameter values

A strategy depends on various parameters. The same strategy may perform differently for different instruments and for different values of the technical indicators. For example, an exponential moving average (EMA) strategy with parameters (time periods) 4 and 9 may perform well for STOCK X, but the same strategy with different parameter values, say 5 and 13, may not perform well for STOCK X, or even the same strategy with the...