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Hands-On Financial Trading with Python

You're reading from Hands-On Financial Trading with Python

Product type Book

Published in Apr 2021

Publisher Packt

ISBN-13 9781838982881

Pages 360 pages

Edition 1st Edition

Languages

Concepts

Authors (2):

Jiri Pik

Sourav Ghosh

View More author details

Table of Contents (15) Chapters

Preface

1. Section 1: Introduction to Algorithmic Trading

2. Chapter 1: Introduction to Algorithmic Trading

3. Section 2: In-Depth Look at Python Libraries for the Analysis of Financial Datasets

4. Chapter 2: Exploratory Data Analysis in Python

5. Chapter 3: High-Speed Scientific Computing Using NumPy

6. Chapter 4: Data Manipulation and Analysis with pandas

7. Chapter 5: Data Visualization Using Matplotlib

8. Chapter 6: Statistical Estimation, Inference, and Prediction

9. Section 3: Algorithmic Trading in Python

10. Chapter 7: Financial Market Data Access in Python

11. Chapter 8: Introduction to Zipline and PyFolio

12. Chapter 9: Fundamental Algorithmic Trading Strategies

13. Other Books You May Enjoy

Appendix A: How to Setup a Python Environment

Importing market data into a Zipline/PyFolio backtesting system

Backtesting depends on us having an extensive market data database.

Zipline introduces two market data-specific terms – bundle and ingest:

A bundle is an interface for incrementally importing market data into Zipline's proprietary database from a custom source.
An ingest is the actual process of incrementally importing the custom source market data into Zipline's proprietary database; the data ingest is not automatically updated. Each time you need fresh data, you must re-ingest the bundle.

By default, Zipline supports these bundles:

Historical Quandl bundle (complimentary daily data for US equities up to 2018)
.csv files bundle

We will now learn how to import these two bundles in more detail.

Importing data from the historical Quandl bundle

First, in the activated zipline_env environment, set the QUANDL_API_KEY environment variable to your free (or paid)...

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Authors (2)

Jiri Pik

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.

See other products by Jiri Pik

Sourav Ghosh

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 with the most liquid global futures contracts. He is currently the vice president at an investment bank based in São Paulo, Brazil. He holds a master's 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.

See other products by Sourav Ghosh

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