Algorithmic Trading with MQL4: Definitive Reference for Developers and Engineers

"Algorithmic Trading with MQL4"

"Algorithmic Trading with MQL4" is a comprehensive guide designed for traders, technologists, and financial engineers seeking to master the art and science of building algorithmic trading systems within the powerful MetaTrader 4 (MT4) platform. This book lays a strong foundation, meticulously exploring the critical evolution of automation in today’s financial markets, key market mechanics, statistical approaches, and the nuanced landscape of risk, compliance, and ethical strategy design. Whether you are new to algorithmic trading or looking to institutionalize your approach, you'll find a clear exposition of the systems development lifecycle, supported by practical context on MT4's unique architecture.

Progressing from core concepts to advanced implementation, the book delivers an in-depth analysis of the MQL4 programming language. Readers are guided through robust trading system architecture, custom indicators, secure integration with external APIs and data feeds, and the intricacies of high-performance code development. Beyond mere scripting, the text explores advanced topics such as error handling, diagnostics, memory management, and the use of machine learning, distributed computation, and hybrid cloud deployments to build and operate cutting-edge, fault-tolerant trading environments.

The final chapters offer a real-world perspective with detailed case studies, security and compliance best practices, and integration with risk analytics and portfolio management systems. Readers benefit from actionable insights on end-to-end system security, operational resilience, global regulatory requirements, and the nuances of live deployment. With a focus on future trends—including the growing influence of decentralized finance and cryptocurrencies—this book empowers practitioners to adapt, innovate, and lead in a rapidly evolving landscape of algorithmic trading.

© 2025 HiTeX Press (eBook): 6610000818334

Data wydania

eBook: 29 maja 2025