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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 C++ Trading Algorithm’s Building Blocks

In this chapter, we will build components that make up the intelligence in our trading applications. These are the components that the trading strategies will rely on very heavily to make decisions, send and manage orders, track and manage positions, profits and losses (PnLs), and manage risk. Not only do the trading strategies need to track the trading PnLs since the goal is to make money, but these components also need to track the PnLs to decide when to stop trading if needed. We will learn how to compute complex features from market data updates, track trading performance based on order executions and market updates, send and manage live strategy orders in the market, and manage market risk. In this chapter, we will cover the following topics:

  • Reacting to executions and managing positions, PnLs, and risk
  • Building the feature engine and computing complex features
  • Using executions and updating positions and...
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