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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 (17) Chapters Close

Mastering Python for Finance
Credits
About the Author
About the Reviewers
www.PacktPub.com
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

Chapter 8. Algorithmic Trading

Algorithmic trading automates the systematic trading process, where orders are executed at the best price possible based on a variety of factors, such as pricing, timing, and volume. Some brokerage firms may offer an application programming interface (API) as part of their service offering to customers who wish to deploy their own trading algorithms. For developing an algorithmic trading system, it must be highly robust and handle any point of failure during the order execution. Network configuration, hardware, memory management and speed, and user experience are some factors to be considered when designing a system in executing orders. Designing larger systems inevitably add complexity to the framework.

As soon as a position in a market is opened, it is subjected to various types of risk, such as market risk. To preserve the trading capital as much as possible, it is important to incorporate risk management measures to the trading system. Perhaps the most...

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