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

Dynamic memory allocation

Allocation in the heap (or dynamic allocation) is common in programming. We need dynamic allocation for the flexibility to allocate at runtime. The operating system implements the dynamic memory management structures, algorithms, and routines. All dynamically allocated memory goes to the heap section of main memory. The OS maintains a few linked lists of memory blocks, primarily the free list to track contiguous blocks of free/unallocated memory and the allocated list to track blocks that have been allocated to the applications. On new memory allocation requests (malloc()/new), it traverses the free list to find a block free enough, then updates the free list (by removing that block) and adds it to the allocated list and then returns the memory block to the program. On memory deallocation requests (free()/delete), it removes the freed block from the allocated list and moves it back to the free list.

Runtime performance penalty

Let's recap the performance...