Development of scalable distributed systems architecture for high-frequency stock trading platforms

Posted: Apr 02, 2010

• Mia Ramirez
• Mia Roberts
• Michael Johnson

Abstract

High-frequency trading has transformed financial markets over the past decade, with algorithmic systems now executing the majority of equity trades in major exchanges. The architectural foundation supporting these systems represents one of the most demanding computational challenges in modern computing, requiring unprecedented combinations of ultra-low latency, absolute reliability, and massive scalability. Current architectures for high-frequency trading platforms predominantly follow centralized or partially distributed models that introduce fundamental limitations in both performance and resilience. These systems typically employ a central matching engine surrounded by distributed components for market data processing and order management, creating inherent bottlenecks and single points of failure that become critically exposed during periods of market stress. The conventional approach to distributed systems in financial trading has been constrained by the CAP theorem's implications, with most implementations prioritizing consistency over availability during network partitions. This prioritization has led to architectures that maintain centralized control over critical functions such as order matching and transaction sequencing. While this ensures financial integrity, it creates systemic vulnerabilities and scalability constraints that become increasingly problematic as trading volumes continue their exponential growth trajectory. The 2010 Flash Crash and subsequent market disruptions have highlighted the fragility of existing architectures when confronted with extreme conditions. This paper presents a fundamentally new architectural paradigm that challenges the established trade-offs between decentralization, consistency, and performance in high-frequency trading systems. Our research was motivated by the observation that natural systems, particularly social insect colonies and flocking behaviors, achieve remarkable coordination, resilience, and scalability without