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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

Volume indicators – volume-weighted average price

Volume-weighted average price (VWAP) is a lagging volume indicator. The VWAP is a weighted moving average that uses the volume as the weighting factor so that higher volume days have more weight. It is a non-cumulative moving average, so only data within the time period is used in the calculation.

Although this function is available in talib, we will show you how to compute an indicator manually here by creating its formula. This will help you create your own indicators at times when you may use customer technical indicators or not-so-popular indicators that are missing from talib.

The formula for calculating VWAP is as follows:

Here, n is the time period and has to be defined by the user.

Getting started

Make sure your Python namespace has the following objects:

  1. pd (module)
  2. plot_candlesticks_chart (function)
  3. PlotType (enum)
  4. historical_data (a pandas DataFrame)

Refer to the Technical requirements section of this chapter to set...

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