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C++ High Performance for Financial Systems: Build efficient and optimized financial systems by leveraging the power of C++ - Couverture souple
L'édition de cet ISBN n'est malheureusement plus disponible.
Synopsis
An in-depth guide covering system architecture, low-latency strategies, risk management, and machine learning for experienced programmers looking to enter the financial industry and build high-performance trading systems
Key Features
- Get started with building financial trading systems
- Focus on scalability, architecture, and implementing low-latency network communication in C++
- Optimize code and use parallel computing techniques for better performance
- Purchase of the print or Kindle book includes a free PDF eBook
Book Description
Unlock the secrets of the finance industry and dive into the world of high-performance trading systems with C++ High Performance for Financial Systems. Trading systems are the backbone of the financial world, and understanding how to build them for optimal performance is crucial for success. If you've ever dreamt of creating scalable and cutting-edge financial software, this guide is your key to success.
A cornerstone of this book is its coverage of system design and architecture. The book starts by outlining the role of C++ in finance and trading. You'll learn the principles and methodologies behind building systems that can handle vast amounts of data, execute complex trading strategies with ease, and maintain the highest levels of reliability. Armed with this knowledge, you'll be equipped to tackle even the most challenging trading scenarios.
In the fast-paced world of finance, every millisecond counts. This book delves into low-latency strategies that will enable your trading systems to react with lightning speed. You’ll also learn the art of reducing latency, optimizing code, and leveraging the latest hardware and software techniques to gain a competitive edge in the market.
By the end of this book, you’ll be well-versed in architecting a financial trading system as well as advanced strategies and new industry trends.
What you will learn
- Design architecture for scalable financial trading systems
- Understand strategies for low-latency trading and high-frequency trading
- Discover how to implement machine learning algorithms for financial data analysis
- Understand risk management techniques for financial trading systems
- Explore advanced topics in finance and trading, including machine learning for algorithmic trading and portfolio optimization
- Get up to speed with best practices for developing financial trading systems with C++
Who this book is for
This book is for experienced C++ developers who want to enter the finance industry and learn how trading systems work. It is also suitable for quantitative analysts, financial engineers, and anyone interested in building scalable and robust trading systems. The book assumes familiarity with the C++ programming language, data structures, and algorithms. Additionally, readers should have a basic understanding of finance and trading concepts, such as market data, trading strategies, and risk management.
Table of Contents
- Introduction
- System Design and Architecture
- High Performance Computing in Financial Systems
- Machine Learning in Financial Systems
- Scalability in Financial Systems
- Low Latency Strategies and Algorithms
- Advanced Topics in Financial Systems
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
À propos de l?auteur
Ariel Silahian is a seasoned software engineer with over 20 years of experience in the industry. With a strong background in C++ and .NET C#, Ariel has honed his technical skills to deliver successful projects for a range of financial institutions, including banks and financial trading companies, both domestically and internationally. Thanks to his passion for high-frequency and electronic trading systems he has developed a deep understanding of financial markets, resulting in his proven track record in delivering top-performing systems from scratch. He has also worked on other critical systems such as monitoring systems, machine learning research, and management decision tree systems, and has received recognition for his exceptional work.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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