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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

Fetching the Japanese candlestick pattern with variations in candle intervals

The historical data of a financial instrument can be analyzed in the form of Japanese candlesticks pattern with varying candle intervals. Brokers typically support candle intervals of 1 minute, 3 minutes, 5 minutes, 10 minutes, 15 minutes, 30 minutes, 1 hour, 1 day, and so on. A shorter candle interval hints at a localized price movement trend, while a larger candle interval indicates an overall price movement trend. Depending on the algorithmic trading strategy, you may need a shorter candle interval or a larger one. A candle interval of 1 minute is often the smallest available candle interval. This recipe demonstrates the historical data of a financial instrument for a duration of a day in various candle intervals.

Getting ready

Make sure the broker_connection object is available in your Python namespace. Refer to the Technical requirements section of this chapter to learn how to set up broker_connection.

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