This is the code repository for Building Low Latency Applications with C++, published by Packt.
Develop a complete low latency trading ecosystem from scratch using modern C++
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.
This book covers the following exciting features:
- Gain insights into the nature of low latency applications across various industries
- Understand how to design and implement low latency applications
- Explore C++ design paradigms and features for low latency development
- Discover which C++ features are best avoided in low latency development
- Implement best practices and C++ features for low latency
- Measure performance and improve latencies in the trading system
If you feel this book is for you, get your copy today!
All of the code is organized into folders. For example, Chapter02.
The code will look like the following:
main:
.LFB1
Movl $100, %edi
Call _Z9factorialj
Following is what you need for this book: This book is for C++ developers who want to gain expertise in low latency applications and effective design and development strategies. C++ software engineers looking to apply their knowledge to low latency trading systems such as HFT will find this book useful to understand which C++ features matter and which ones to avoid. Quantitative researchers in the trading industry eager to delve into the intricacies of low latency implementation will also benefit from this book. Familiarity with Linux and the C++ programming language is a prerequisite for this book.
With the following software and hardware list you can run all code files present in the book (Chapter 1-15).
| Chapter | Software required | OS required |
|---|---|---|
| 1 | C++ 20 | Linux |
| 2 | GCC 11.3.0 | Linux |
We also provide a PDF file that has color images of the screenshots/diagrams used in this book. Click here to download it.
Sourav Ghosh has worked in several proprietary high-frequency algorithmic trading firms over the last decade. He has built and deployed extremely low latency, high throughput automated trading systems for trading exchanges around the world, across multiple asset classes. He specializes in statistical arbitrage market-making, and pairs trading strategies for the most liquid global futures contracts. He works as a Senior Quantitative Developer at a trading firm in Chicago. He holds a Masters in Computer Science from the University of Southern California. His areas of interest include Computer Architecture, FinTech, Probability Theory and Stochastic Processes, Statistical Learning and Inference Methods, and Natural Language Processing.