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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

Summary

This chapter showed that JVM eases software developers' lives but impedes a trading system's performance. We demonstrated that by understanding how the JVM behaves under the hood, following good coding practice, and tuning the JVM, we could use Java as a serious programming language candidate for HFT. We studied in detail how to measure performance with Java. We know that measuring the execution time is the only evidence that code performs better after optimization. As we did with C++, we introduced high-performance data structures helping to get a performant code. We combined these data structures with the use of threads and thread pools. We concluded by discussing logging and database access, which are vital in HFT.

C++ and Java are the most used languages in HFT. The next chapter will talk about another programming language: Python. We will see how Python can be used in HFT and run fast using external libraries.

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