Book Image

Building Low Latency Applications with C++

By : Sourav Ghosh
5 (1)
Book Image

Building Low Latency Applications with C++

5 (1)
By: Sourav Ghosh

Overview of this book

C++ is meticulously designed with efficiency, performance, and flexibility as its core objectives. However, real-time low latency applications demand a distinct set of requirements, particularly in terms of performance latencies. With this book, you’ll gain insights into the performance requirements for low latency applications and the C++ features critical to achieving the required performance latencies. You’ll also solidify your understanding of the C++ principles and techniques as you build a low latency system in C++ from scratch. You’ll understand the similarities between such applications, recognize the impact of performance latencies on business, and grasp the reasons behind the extensive efforts invested in minimizing latencies. Using a step-by-step approach, you’ll embark on a low latency app development journey by building an entire electronic trading system, encompassing a matching engine, market data handlers, order gateways, and trading algorithms, all in C++. Additionally, you’ll get to grips with measuring and optimizing the performance of your trading system. By the end of this book, you’ll have a comprehensive understanding of how to design and build low latency applications in C++ from the ground up, while effectively minimizing performance latencies.
Table of Contents (19 chapters)
1
Part 1:Introducing C++ Concepts and Exploring Important Low-Latency Applications
6
Part 2:Building a Live Trading Exchange in C++
10
Part 3:Building Real-Time C++ Algorithmic Trading Systems
14
Part 4:Analyzing and Improving Performance

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...