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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

The recorded close price of the last traded day of a financial instrument

Often, trading strategies use the previous day's closing price of a financial instrument as one of the first qualifying conditions before making decisions to place trades. Comparing the current day's opening price with the previous day’s close price may give a hint as to whether the market price is bound to rise or fall for the current day for an instrument. If the open price is significantly higher than the previous day's close price, the price may continue to rise for the day. Similarly, if the open price is significantly lower than the previous day's close price, the price may continue to fall for the day. The recorded close price data is static in nature, meaning it does not change during the live trading hours. This recipe shows how to fetch the previous day's close price of a financial instrument.

Getting ready

Make sure the broker_connection and instrument1 objects are available...

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