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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
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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

Volatility indicators – Bollinger Bands

Bollinger Bands are a lagging volatility indicator. Bollinger Bands consist of three lines, or bands—the middle band, the lower band, and the upper band. The gap between the bands widens when the price volatility is high and reduces when the price volatility is low.

Bollinger Bands are an indicator of overbought or oversold conditions. When the price is near the upper band or the lower band, this indicator predicts that a reversal will happen soon. The middle band acts as a support or resistance level.

The upper band and lower band can also be interpreted as price targets. When the price bounces off of the upper band and crosses the middle band, the lower band becomes the price target, and vice versa.

The formulae for computing the Bollinger Bands are as follows.

Bollinger Bands define the typical price (TP) as the average of the high, low, and close of a candle. The TP is used for computing the middle band, lower band, and upper...

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