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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

Summary

In this chapter, we were introduced to the evolution of trading from the pits to the electronic trading platform, and learned how algorithmic trading came about. We looked at some brokers offering API access to their trading service offering. To help us get started on our journey in developing an algorithmic trading system, we used the TWS of IB and the IbPy Python module.

In our first trading program, we successfully sent an order to our broker through the TWS API using a demonstration account. Next, we developed a simple algorithmic trading system. We started by requesting the market data and account updates from the server. With the captured real-time information, we implemented a mean-reverting algorithm to trade the markets. Since this trading system uses only one indicator, more work would be required to build a robust, reliable, and profitable trading system.

We also discussed currency trading with the OANDA REST API with the help of the oandapy Python module. After setting...

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