Hands-On Financial Trading with Python: A practical guide to using Zipline and other Python libraries for backtesting trading strategies

by Jiri Pik, Sourav Ghosh

Overview

Creating an effective system to automate your trading can help you achieve two of every trader’s key goals; saving time and making money. But to devise a system that will work for you, you need guidance to show you the ropes around building a system and monitoring its performance. This is where Hands-on Financial Trading with Python can give you the advantage.

This practical Python book will introduce you to Python and tell you exactly why it’s the best platform for developing trading strategies. You’ll then cover quantitative analysis using Python, and learn how to build algorithmic trading strategies with Zipline using various market data sources.

Using Zipline as the backtesting library allows access to complimentary US historical daily market data until 2018. As you advance, you will gain an in-depth understanding of Python libraries such as NumPy and pandas for analyzing financial datasets, and explore Matplotlib, statsmodels, and scikit-learn libraries for advanced analytics.

As you progress, you’ll pick up lots of skills like time series forecasting, covering pmdarima and Facebook Prophet.
By the end of this trading book, you will be able to build predictive trading signals, adopt basic and advanced algorithmic trading strategies, and perform portfolio optimization to help you get —and stay—ahead of the markets.

Product Details

ISBN-13:	9781838988807
Publisher:	Packt Publishing
Publication date:	04/29/2021
Sold by:	Barnes & Noble
Format:	eBook
Pages:	360
File size:	12 MB
Note:	This product may take a few minutes to download.

About the Author

Jiri Pik is an artificial intelligence architect & strategist who works with major investment banks, hedge funds, and other players. He has architected and delivered breakthrough trading, portfolio, and risk management systems, as well as decision support systems, across numerous industries. Jiri's consulting firm, Jiri Pik—RocketEdge, provides its clients with certified expertise, judgment, and execution at the speed of light.


Sourav Ghosh has worked in several proprietary high-frequency algorithmic trading firms over the last decade. He has built and deployed extremely low latency, high throughput automated trading systems for trading exchanges around the world, across multiple asset classes. He specializes in statistical arbitrage market-making, and pairs trading strategies for the most liquid global futures contracts. He works as a Senior Quantitative Developer at a trading firm in Chicago. He holds a Masters in Computer Science from the University of Southern California. His areas of interest include Computer Architecture, FinTech, Probability Theory and Stochastic Processes, Statistical Learning and Inference Methods, and Natural Language Processing.

Table of Contents

Table of Contents

1. Introduction to algorithmic trading
2. Exploratory Data Analysis in Python
3. High-speed Scientific Computing using NumPy
4. Data Manipulation and Analysis with Pandas
5. Data Visualization using Matplotlib
6. Statistical Estimation, Inference, and Prediction
7. Financial Market Data Access in Python
8. Introduction to Zipline and PyFolio
9. Fundamental algorithmic trading strategies