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Python Algorithmic Trading Cookbook

You're reading from   Python Algorithmic Trading Cookbook All the recipes you need to implement your own algorithmic trading strategies in Python

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Product type Paperback
Published in Aug 2020
Publisher Packt
ISBN-13 9781838989354
Length 542 pages
Edition 1st Edition
Languages
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Author (1):
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Pushpak Dagade Pushpak Dagade
Author Profile Icon Pushpak Dagade
Pushpak Dagade
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Toc

Table of Contents (16) Chapters Close

Preface 1. Handling and Manipulating Date, Time, and Time Series Data 2. Stock Markets - Primer on Trading FREE CHAPTER 3. Fetching Financial Data 4. Computing Candlesticks and Historical Data 5. Computing and Plotting Technical Indicators 6. Placing Regular Orders on the Exchange 7. Placing Bracket and Cover Orders on the Exchange 8. Algorithmic Trading Strategies - Coding Step by Step 9. Algorithmic Trading - Backtesting 10. Algorithmic Trading - Paper Trading 11. Algorithmic Trading - Real Trading 12. Other Books You May Enjoy Appendix I
1. Appendix II
2. Appendix III

Querying a list of exchanges

An exchange is a marketplace where instruments are traded. Exchanges ensure that the trading process is fair and happens in an orderly fashion at all times. Usually, a broker supports multiple exchanges. This recipe demonstrates how to find the list of exchanges supported by the broker.

Getting ready

Make sure the instruments object is available in your Python namespace. Refer to the second recipe of this chapter to learn how to set up this object.

How to do it…

Display the exchanges supported by the broker:

>>> exchanges = instruments.exchange.unique()
>>> print(exchanges)

You will get the following output:

['BCD' 'BSE' 'NSE' 'CDS' 'MCX' 'NFO']

How it works…

instruments.exchange returns a pandas.Series object. Its unique() method returns a numpy.ndarray object consisting of unique exchanges supported by the broker.

You have been reading a chapter from
Python Algorithmic Trading Cookbook
Published in: Aug 2020
Publisher: Packt
ISBN-13: 9781838989354
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