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Building Low Latency Applications with C++

You're reading from   Building Low Latency Applications with C++ Develop a complete low latency trading ecosystem from scratch using modern C++

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Product type Paperback
Published in Jul 2023
Publisher Packt
ISBN-13 9781837639359
Length 506 pages
Edition 1st Edition
Languages
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Author (1):
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Sourav Ghosh Sourav Ghosh
Author Profile Icon Sourav Ghosh
Sourav Ghosh
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Table of Contents (19) Chapters Close

Preface 1. Part 1:Introducing C++ Concepts and Exploring Important Low-Latency Applications
2. Chapter 1: Introducing Low Latency Application Development in C++ FREE CHAPTER 3. Chapter 2: Designing Some Common Low Latency Applications in C++ 4. Chapter 3: Exploring C++ Concepts from A Low-Latency Application’s Perspective 5. Chapter 4: Building the C++ Building Blocks for Low Latency Applications 6. Part 2:Building a Live Trading Exchange in C++
7. Chapter 5: Designing Our Trading Ecosystem 8. Chapter 6: Building the C++ Matching Engine 9. Chapter 7: Communicating with Market Participants 10. Part 3:Building Real-Time C++ Algorithmic Trading Systems
11. Chapter 8: Processing Market Data and Sending Orders to the Exchange in C++ 12. Chapter 9: Building the C++ Trading Algorithm’s Building Blocks 13. Chapter 10: Building the C++ Market Making and Liquidity Taking Algorithms 14. Part 4:Analyzing and Improving Performance
15. Chapter 11: Adding Instrumentation and Measuring Performance 16. Chapter 12: Analyzing and Optimizing the Performance of Our C++ System 17. Index 18. Other Books You May Enjoy

Building the feature and computing complex features

In this section, we will build a minimal version of a feature engine. We will only compute two simple features – one (market price) that computes fair market prices based on the top of book prices and quantity and another (aggressive trade qty ratio) that computes how big a trade is compared to the top of book quantities. We will use these feature values to drive our market-making and liquidity-taking trading algorithms later in this chapter. The source code for the FeatureEngine class we will build here can be found in the Chapter9/trading/strategy/feature_engine.h file on GitHub. We discussed the details of this component in Chapter, Designing Our Trading Ecosystem, in the Designing a framework for low-latency C++ trading algorithms section.

Defining the data members in the feature engine

First, we need to declare the FeatureEngine class and define the data members inside this class. First, we will include the required...

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