The Evolution of Algo and Prop Trading in Derivatives: Insights from the Canadian Derivatives Conference 2025
As algorithmic trading and AI continue to reshape the global financial landscape, industry leaders gathered at the Canadian Annual Derivatives Conference in Montreal to discuss the latest trends, risks, and opportunities in derivatives trading.
One standout session focused on the evolution of algorithmic and proprietary trading firms, offering valuable insight into the realities of deploying AI, managing latency, improving risk frameworks, and navigating a potential shift toward 24/7 trading.
Here are the key takeaways.
AI in Derivatives Trading: From Buzzword to Business Tool
A decade ago, AI in trading was more theory than practice. Today, it’s a strategic differentiator.
Panelists highlighted how AI and machine learning are now actively used to forecast market movements, improve model calibration, generate trading ideas, and stress test portfolios. The focus has shifted from experimentation to deployment, with firms building tailored, private AI environments to avoid data leakage and retain intellectual property.
Crucially, they emphasized that speed matters, especially when it comes to inference. Deploying lightweight models such as LSTMs directly into FPGAs—rather than traditional GPU or software-based environments—was presented as a way to drastically reduce latency and gain real-time insights without compromising on data security.
Risk Management Is Now a Competitive Advantage
Algorithmic trading is no longer the Wild West. In fact, it now resembles mission control, with firms prioritizing robust pre-trade and firm-wide risk frameworks.
Panelists outlined a multi-tiered risk architecture that includes:
- Order-level risk checks (e.g., max order size, fat-finger prevention)
- Security-level checks (e.g., limits on the number of orders per instrument)
- Firm-level controls (e.g., max exposure or capital-at-risk thresholds)
Modern systems must deliver real-time decisions without introducing latency, and some firms are now embedding risk checks directly into FPGAs to avoid bottlenecks. The key message: If your risk checks are slow, your trading edge is gone.
Is 24/7 Derivatives Trading the Next Frontier?
The panel also tackled the hot-button topic of 24/7 trading. With crypto and FX already operating around the clock, is it time for derivatives to follow?
Infrastructure-wise, firms are ready. Many systems are already supporting continuous uptime across asset classes. However, liquidity, staffing, and risk during off-hours remain real concerns.
Panelists were aligned on this: while technology is not the blocker, human factors and market participation are. For interest rate products in particular, expanding to 24/5 trading may be a more realistic intermediate step. The benefits—like access to global liquidity—must be balanced with the operational risk of extended trading hours.
The Regulatory Landscape: What’s Next for AI in Trading?
As trading firms integrate AI into execution and strategy, regulators are adapting as well.
Panelists noted that some regulators are using AI tools themselves to monitor market behavior and detect anomalies in real time. They’re beginning to leverage large historical datasets and live feeds to enforce compliance proactively—not just reactively.
One key difference discussed was between retail and institutional AI use:
- For retail-facing applications, AI explainability will likely become mandatory.
- For institutional desks, results and compliance matter more than the “how” behind a model’s decision-making—provided someone takes ownership of the output.
Final Thoughts
The world of algorithmic and proprietary trading is accelerating fast. From AI-powered signal generation to real-time, low-latency risk frameworks and the growing pressure to accommodate 24/7 global markets, the message is clear: standing still is not an option.
Firms that succeed will be those that blend innovation with discipline—harnessing AI, automation, and infrastructure without losing sight of governance and risk.
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