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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
2. Overview of Financial Analysis with Python FREE CHAPTER 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

Summary

A backtest is a simulation of a model-driven investment strategy's response to historical data. The purpose of performing experiments with backtests is to make discoveries about a process or system and to compute various factors related to either risk or return. The factors are typically used together to find a combination that is predictive of the return.

While working on designing and developing a backtest, it would be helpful to think in terms of the concept of creating video games. In a virtual trading environment, components are needed for the simulation of price feeds, the order-matching engine, the order book management, as well as functions for account and position updates. To achieve these functionalities, we can explore the concept of an event-driven backtesting system.

In this chapter, we designed and implemented a backtesting system that interacts with...

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