High-frequency trading surveillance: challenges and solutions
In this article, we'll look at the challenges of high-frequency trading surveillance, risks, and the tools needed to detect abuse.
High-frequency trading (HFT) is once again a top priority for regulators. In this article, we examine why HFT surveillance is complex, what risks regulators are focusing on in 2025, and the capabilities firms need to identify abusive behaviour at speed.
Why HFT is back in the regulatory spotlight in 2025
High-frequency trading (HFT) has been part of the market landscape for years, but the scale and sophistication of today’s strategies are pushing regulators to raise the bar.
The Market Abuse Regulation (MAR) in the EU, the Securities and Exchange Commission (SEC) and the Commodity Futures Trading Commission (CFTC) in the US, and the Australian Securities and Investments Commission (ASIC) and the Monetary Authority of Singapore (MAS) in the Asia-Pacific (APAC) are tightening oversight of algorithmic trading practices, with a focus on speed-driven abuse patterns.
The risks aren’t theoretical. Recent enforcement cases show that even compliant algorithms can create manipulative market effects if not monitored properly. With trade volumes measured in microseconds, traditional surveillance systems simply can’t keep up.
Understanding the HFT surveillance challenges
HFT amplifies surveillance complexity in three main ways:
- Data velocity – Millions of orders and cancellations per second overwhelm legacy systems.
- Latency sensitivity – Even nanosecond delays in detection can mean missing the manipulation window.
- Pattern subtlety – Abuse can look like normal liquidity provision until patterns emerge over thousands of trades.
For example, quote stuffing floods the market with orders that are cancelled almost immediately, distorting price discovery. Latency arbitrage exploits speed advantages to trade ahead of slower participants. Layering at scale involves placing multiple non-bona fide orders to move the price in a desired direction.
These patterns can span multiple venues and asset classes, making multi-venue coverage essential.
Building effective HFT surveillance
To monitor HFT successfully, firms need a combination of real-time detection and detailed post-trade analysis. Modern surveillance systems must be capable of doing more than just basic rule sets, and also support precision tracking at scale.
The essential capabilities of a detection toolkit include:
- Ultra-low latency data capture with time-stamping precision down to microseconds.
- Order lifecycle tracking to monitor placement, modification, and cancellation patterns.
- Venue linkage to connect related activity across lit, dark, and alternative trading systems.
- Behavioural modelling to distinguish between legitimate market making and manipulative intent.
- Real-time alerting for high-risk patterns such as quote stuffing, layering, and spoofing.
- Explainable AI models to satisfy regulator demands for transparency in detection logic.
Looking ahead: global HFT oversight
Expect regulators to tighten algo governance standards, increase penalties for abusive patterns, and demand greater AI explainability. Firms operating across jurisdictions should align with the strictest applicable rules now to avoid future retrofits.
HFT isn’t going away, but neither is the regulatory pressure to monitor it effectively. By combining ultra-fast detection, behavioural modelling, and explainable AI, firms can meet regulatory expectations and protect market integrity.
Book a demo to see how Trapets can equip your surveillance team with the technology needed for modern markets.