Book Image

Developing High-Frequency Trading Systems

By : Sebastien Donadio, Sourav Ghosh, Romain Rossier
5 (1)
Book Image

Developing High-Frequency Trading Systems

5 (1)
By: Sebastien Donadio, Sourav Ghosh, Romain Rossier

Overview of this book

The world of trading markets is complex, but it can be made easier with technology. Sure, you know how to code, but where do you start? What programming language do you use? How do you solve the problem of latency? This book answers all these questions. It will help you navigate the world of algorithmic trading and show you how to build a high-frequency trading (HFT) system from complex technological components, supported by accurate data. Starting off with an introduction to HFT, exchanges, and the critical components of a trading system, this book quickly moves on to the nitty-gritty of optimizing hardware and your operating system for low-latency trading, such as bypassing the kernel, memory allocation, and the danger of context switching. Monitoring your system’s performance is vital, so you’ll also focus on logging and statistics. As you move beyond the traditional HFT programming languages, such as C++ and Java, you’ll learn how to use Python to achieve high levels of performance. And what book on trading is complete without diving into cryptocurrency? This guide delivers on that front as well, teaching how to perform high-frequency crypto trading with confidence. By the end of this trading book, you’ll be ready to take on the markets with HFT systems.
Table of Contents (16 chapters)
1
Part 1: Trading Strategies, Trading Systems, and Exchanges
5
Part 2: How to Architect a High-Frequency Trading System
10
Part 3: Implementation of a High-Frequency Trading System

Removing runtime decisions

As C++ is a compiled language, it can optimize the source code during the compilation process and generate machine code with as much code and data resolved at compile time. In this section, we will look at the motivation for removing runtime decisions, consider some C++ constructs that are resolved at runtime, and see how an ultra-low latency HFT application tries to minimize or substitute runtime decisions.

Motivation for removing runtime decisions

The more code that lies on the critical path and can be resolved at compile time (instead of being resolved at runtime), the better the application performance – a key element in optimizing HFT applications. Here we discuss the advantages obtained by the compiler, CPUs, and memory architecture in terms of performance when the application has minimal runtime decisions and most of the code can be resolved at compile time.

Compiler optimizations

If the compiler can resolve the source and constant...