Market Data Architecture & Quant Systems Design: Building Time-Series Databases, Execution Engines, and Risk Analytics Pipelines for Institutional Trading by James Preston, Hayden Van Der Post, Vincent Bisette
English | January 19, 2026 | ISBN: N/A | ASIN: B0GHPTFTKL | 501 pages | EPUB | 0.63 Mb
Reactive Publishing
Market Data Architecture & Quant Systems Design delivers a comprehensive blueprint for designing modern institutional trading infrastructure in an era defined by latency, scale, and real-time analytics. Written for quantitative engineers, financial data architects, and advanced practitioners in electronic trading, the book maps the full lifecycle of market data through acquisition, transformation, storage, analysis, and execution.
Readers will learn how to engineer high-performance time-series databases, event-driven execution engines, and resilient risk analytics pipelines capable of supporting both discretionary and algorithmic strategies. James Preston walks through the core disciplines necessary for modern capital markets technology, including message parsing, clock synchronization, exchange semantics, microstructure, data normalization, pricing models, caching, serialization, concurrency, and system monitoring.
Through detailed technical frameworks and real-world design patterns, the book examines:
* Market data ingestion and normalization across equities, FX, futures, and digital assets
* Tick-level storage, compression, and time-series database architecture
* Low-latency execution engine design for algorithmic trading
* Risk, P&L, and portfolio analytics pipelines that operate in real time
* Distributed system design, concurrency control, and resiliency engineering
* Infrastructure and deployment models for institutional environments
* Observability, performance profiling, and system reliability
* Integrating quantitative models and risk engines into production systems
* End-to-end architecture for multi-asset trading platforms
The result is a technical reference that bridges quantitative finance, computer science, and systems engineering. Whether building a proprietary prop-trading stack, modernizing internal market data workflows, or architecting analytics platforms for institutions, this book provides both the conceptual foundations and implementation detail required to operate at scale.
Market Data Architecture & Quant Systems Design positions the practitioner to understand not just how individual components work, but how the entire trading ecosystem fits together, data to decision to execution.
Links are Interchangeable - Single Extraction
