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

Computing and managing risk

The final component we still need to build before we can build our trading strategies is RiskManager. The RiskManager component tracks the active order quantities that a trading strategy has in the market through the same OrderManager instance that a trading strategy uses. It also tracks the positions and realized and unrealized PnLs using the PositionKeeper instance, which tracks the trading strategy’s positions and PnLs. It checks that the strategy stays within its assigned risk limits. If the trading strategy goes past its risk limits, such as if it loses more money than it’s allowed, tries to send an order larger than it’s allowed, or builds a position larger than it’s allowed, it prevents it from trading. To keep our RiskManager simple, we will only implement risk checks on the maximum allowed order size, the maximum allowed position, and the maximum allowed loss for each trading instrument in the client’s trading...