  This work aims to bridge the existing knowledge gap in the optimisation of
latency-critical code, specifically focusing on high-frequency trading (HFT)
systems. The research culminates in three main contributions: the creation of a
Low-Latency Programming Repository, the optimisation of a market-neutral
statistical arbitrage pairs trading strategy, and the implementation of the
Disruptor pattern in C++. The repository serves as a practical guide and is
enriched with rigorous statistical benchmarking, while the trading strategy
optimisation led to substantial improvements in speed and profitability. The
Disruptor pattern showcased significant performance enhancement over
traditional queuing methods. Evaluation metrics include speed, cache
utilisation, and statistical significance, among others. Techniques like Cache
Warming and Constexpr showed the most significant gains in latency reduction.
Future directions involve expanding the repository, testing the optimised
trading algorithm in a live trading environment, and integrating the Disruptor
pattern with the trading algorithm for comprehensive system benchmarking. The
work is oriented towards academics and industry practitioners seeking to
improve performance in latency-sensitive applications.
