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Mastering Python for Finance

You're reading from   Mastering Python for Finance Implement advanced state-of-the-art financial statistical applications using Python

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Product type Paperback
Published in Apr 2019
Publisher Packt
ISBN-13 9781789346466
Length 426 pages
Edition 2nd Edition
Languages
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Author (1):
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James Ma Weiming James Ma Weiming
Author Profile Icon James Ma Weiming
James Ma Weiming
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Toc

Table of Contents (16) Chapters Close

Preface 1. Section 1: Getting Started with Python FREE CHAPTER
2. Overview of Financial Analysis with Python 3. Section 2: Financial Concepts
4. The Importance of Linearity in Finance 5. Nonlinearity in Finance 6. Numerical Methods for Pricing Options 7. Modeling Interest Rates and Derivatives 8. Statistical Analysis of Time Series Data 9. Section 3: A Hands-On Approach
10. Interactive Financial Analytics with the VIX 11. Building an Algorithmic Trading Platform 12. Implementing a Backtesting System 13. Machine Learning for Finance 14. Deep Learning for Finance 15. Other Books You May Enjoy

Building an Algorithmic Trading Platform

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. Brokerage firms may offer an Application Programming Interface (API) as part of their service offering for customers who wish to deploy their own trading algorithms. An algorithmic trading system must be highly robust to handle any point of failure during the order execution. Network configuration, hardware, memory management, speed, and user experience are a number of factors to be considered when designing a system for executing orders. Designing larger systems inevitably adds more 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, interest rate risk, and liquidity risk...

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