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Mastering Python for Finance

You're reading from   Mastering Python for Finance Understand, design, and implement state-of-the-art mathematical and statistical applications used in finance with Python

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Product type Paperback
Published in Apr 2015
Publisher Packt
ISBN-13 9781784394516
Length 340 pages
Edition 1st Edition
Languages
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Toc

Table of Contents (12) Chapters Close

Preface 1. Python for Financial Applications FREE CHAPTER 2. The Importance of Linearity in Finance 3. Nonlinearity in Finance 4. Numerical Procedures 5. Interest Rates and Derivatives 6. Interactive Financial Analytics with Python and VSTOXX 7. Big Data with Python 8. Algorithmic Trading 9. Backtesting 10. Excel with Python Index

Algorithmic trading with Interactive Brokers and IbPy


In this section, we will build a working algorithmic trading platform that will authenticate with Interactive Brokers (IB) and log in, retrieve the market data, and send orders. IB is one of the most popular brokers in the trading community and has a long history of API development. There are plenty of articles on the use of the API available on the Web. IB serves clients ranging from hedge funds to retail traders. Although the API does not support Python directly, Python wrappers such as IbPy are available to make the API calls to the IB interface. The IB API is unique to its own implementation, and every broker has its own API handling methods. Nevertheless, the documents and sample applications provided by your broker would demonstrate the core functionality of every API interface that can be easily integrated into an algorithmic trading system if designed properly.

Getting Interactive Brokers' Trader WorkStation

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