C++ Techniques and Design Patterns for Low-Latency Trading Systems

Summary

This work examines ways to reduce latency in performance-sensitive C++ applications, with high-frequency trading as its main setting. It describes a programming repository with benchmarked examples, an optimized market-neutral statistical arbitrage pairs strategy, and a C++ implementation of the Disruptor pattern for coordinating concurrent work.

The evaluation considers speed, cache use, and statistical significance. The authors report that cache warming and compile-time evaluation with constexpr produced the clearest latency gains, while the Disruptor outperformed traditional queueing approaches. The trading strategy was also reported to improve in speed and profitability, although the excerpt gives no measurements or experimental details to assess those claims. Live-market testing and integration of the Disruptor with the trading algorithm remain proposed next steps, so the results do not establish end-to-end live performance.

Key ideas

• The work combines practical C++ optimization examples with statistical benchmarking for latency-sensitive applications.
• It applies low-latency techniques to a market-neutral statistical arbitrage pairs strategy.
• The Disruptor pattern is presented as a faster alternative to conventional queueing methods.
• Cache warming and constexpr are reported as especially effective for reducing latency.
• Live trading and integrated system testing remain future work.

Tags

# C++ Design Patterns for Low-latency Applications Including High-frequency Trading


# C++ Design Patterns for Low-latency Applications Including High-frequency Trading









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.

Shown in full with attribution under the source's licence. Licence: abstract CC0

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.