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Developing High-Frequency Trading Systems

Developing High-Frequency Trading Systems

By : Sebastien Donadio, Sourav Ghosh, Romain Rossier
4.2 (19)
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Developing High-Frequency Trading Systems

Developing High-Frequency Trading Systems

4.2 (19)
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)
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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

Java threading

Threads are the basic unit of concurrency in Java. Threads provide the advantage of reducing program execution time by allowing your program to either execute multiple tasks in parallel or execute on one portion of the job while another waits for something to happen (typically input/output (I/O)).

HFT architecture heavily uses threads to increase the throughput, as we mentioned in Chapter 7, HFT Optimization – Logging, Performance, and Networking. Multiple threads are created to do tasks in parallel. Adding threads to a program that is completely CPU bound can only slow it down. Adding threads may assist if it's totally or partially I/O bound, but there's a trade-off to consider between the overhead of adding threads and the increased work that will be done. We know that the underlying hardware (CPU and memory resource) will limit this throughput. If we increase the number of threads beyond a certain limit (such as the number of cores or the number...

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