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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
Tools
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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

The total pending sell quantity of a financial instrument

The total pending sell quantity for a financial instrument is the sum total of the quantity of all pending sell orders available at an instant. This data is dynamic in nature and may change at any moment during the live trading hours.

Getting ready

Make sure the broker_connection and instrument1 objects are available in your Python namespace. Refer to the Technical requirements section of this chapter to set up broker_connection. Refer to the Attributes of a financial instrument recipe of this chapter to set up instrument1.

How to do it…

Fetch and print the total pending sell quantity of instrument1:

>>> total_pending_sell_quantity = \
broker_connection.get_total_pending_sell_quantity(instrument1)
>>> print(f'Total pending SELL quantity: {total_pending_sell_quantity}')

We get the following output (your output may differ):

Total pending SELL quantity: 968602

How it works…

The get_total_pending_sell_quantity...

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