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Python Algorithmic Trading Cookbook: All the recipes you need to implement your own algorithmic trading strategies in Python
75% of respondents would recommend this to a friend
NZD 80
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What Stands Out
Product Details
| Publisher | Packt Publishing |
| Publication date | August 28, 2020 |
| Language | English |
| Print length | 542 pages |
| ISBN-10 | 1838989358 |
| ISBN-13 | 978-1838989354 |
| Item Weight | 2.03 pounds (920 grams) |
| Dimensions | 7.5 x 1.23 x 9.25 inches (19.1 x 3.1 x 23.5 cm) |
Who Should Buy?
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Aspiring Traders
Those looking to develop their own trading strategies will find practical guidance and insights in this cookbook.
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Python Developers
Developers familiar with Python can leverage the recipes to implement advanced trading algorithms effectively.
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Data Analysts
Analysts interested in market trends and trading metrics can utilize the cookbook for data-driven trading strategies.
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Complete Beginners
Novices in both trading and Python may struggle without prior knowledge, as the content assumes some expertise.
Product Description
Python Algorithmic Trading Cookbook: All the recipes you need to implement your own algorithmic trading strategies in Python
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Data Modeling & Design Editorial Review
The Python Algorithmic Trading Cookbook is a comprehensive guide to implementing algorithmic trading strategies using Python. The book begins with an introduction to Jupyter Notebook and data processing, leading on to addressing Broker Interface, and candle plotting. The book provides several chapters on submitting various types of Broker requests and evaluating their responses. However, it does not include any information on selecting investment entities or predicting buy/sell operations. The book has received high praises from customers who found it helpful in starting with Python language for trading. It has well-explained concepts and is easy to follow, making it ideal for individuals new to Python.
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Pros
- Comprehensive guide to implementing algorithmic trading strategies using Python.
- Provides an introduction to Jupyter Notebook and data processing.
- Well-explained concepts make it easy to follow, making it ideal for beginners.
Cons
- Does not include information on selecting investment entities or predicting buy/sell operations.
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