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Hands-On Financial Trading with Python

You're reading from   Hands-On Financial Trading with Python A practical guide to using Zipline and other Python libraries for backtesting trading strategies

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Product type Paperback
Published in Apr 2021
Publisher Packt
ISBN-13 9781838982881
Length 360 pages
Edition 1st Edition
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Authors (2):
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Sourav Ghosh Sourav Ghosh
Author Profile Icon Sourav Ghosh
Sourav Ghosh
Jiri Pik Jiri Pik
Author Profile Icon Jiri Pik
Jiri Pik
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Toc

Table of Contents (15) Chapters Close

Preface 1. Section 1: Introduction to Algorithmic Trading FREE CHAPTER
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

Exploring the IEX Cloud data source

IEX Cloud is one of the commercial offerings. It offers a plan for individuals at USD 9 per month. It also offers a free plan, with a limit of 50,000 API calls per month.

The installation of the Python library is standard:

pip install iexfinance

The full library's documentation is available at https://addisonlynch.github.io/iexfinance/stable/index.html.

The following code is designed to retrieve all symbols:

from iexfinance.refdata import get_symbols
get_symbols(output_format='pandas', token="XXXXXX")
symbol  exchange  exchangeSuffix  exchangeName  name  date  type  iexId  region  currency  isEnabled  figi  cik  lei
0  A  NYS  UN  NEW YORK STOCK EXCHANGE, INC.  Agilent Technologies Inc.  2020-12-29  cs  ...
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