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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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Toc

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

Reacting to executions and managing positions, PnLs, and risk

We need to build a few basic building blocks that will build and support our trading strategies. We discussed the need for these components in Chapter, Designing Our Trading Ecosystem, in the Designing a framework for low-latency C++ trading algorithms section. We have already implemented a major component – the limit order book – but in this section, we will build the remaining components we need, namely the following:

  • A FeatureEngine, which will be used to compute simple and complex features/signals that drive the trading strategy decisions
  • A PositionKeeper, which will receive executions and compute important measures such as position, PnLs, traded volumes, and more
  • An OrderManager, which will be used by the strategies to send orders, manage them, and update these orders when there are updates
  • A RiskManager to compute and check the market risk that a trading strategy is attempting to take...
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