At the start of every year, we do the same thing before we scale exposure or introduce changes: we run a full risk review.
Markets change. Liquidity changes. Correlations change. What worked last year can break quickly. The goal of this review is not to “predict” the year. It is to make sure every strategy we run has clear limits, clear monitoring, and clear accountability.
When you log into our platform, you’ll see four environments:
Different tools, different objectives, different risks. The one thing they share is this: we treat risk like a first-class product feature, not an afterthought.
Below is the checklist we use at the beginning of the year to stress-test each strategy before we deploy capital.
AI is powerful, but it is not magic. We use it to improve speed, consistency, and detection. We do not use it as a substitute for governance.
In practical terms, that means AI helps with things like:
But AI does not get a blank cheque. Strategy changes, sizing, and exposure decisions operate inside rules that are defined and reviewed by a team.
Before anything else, we define the job: growth, income, hedging, or tactical trading. We match the strategy to the client’s objective, time horizon, and drawdown tolerance.
If a strategy does not fit the mandate, it does not matter how “good” it looks on paper.
Every strategy has caps. Limits by instrument, sector, theme, and overall portfolio exposure exist for a simple reason: no single idea should be able to dominate the outcome.
We also define what “too concentrated” looks like and we enforce it.
We plan the exit before the entry.
This includes normal market conditions and stress conditions. We look at how quickly positions can be reduced without unacceptable slippage, and we avoid building positions that only work if liquidity stays perfect.
We stress-test portfolios across regimes, not just one base case.
Examples include rate shocks, volatility spikes, equity drawdowns, FX moves, and correlation breaks. The point is to understand what hurts and how quickly it hurts.
Where risk sits matters.
We review counterparties, venues, and operational dependencies. Concentration is managed so that an issue in one place does not become a platform-wide problem.
Even a strong strategy can be ruined by poor execution.
We monitor spreads, slippage, and fill quality. If execution quality deteriorates, the system should not keep trading at the same size out of habit. It should step down.
This is the part most platforms skip, and it is where problems start.
We review what data is used, what the model is designed to do, and what it is not designed to do. We also enforce version control and change discipline. If a model changes, we document it, review it, and validate it before it affects client capital.
Some decisions should never be “silent.”
We use AI for insight and detection, but the responsibility sits with people. Strategy adjustments and parameter changes follow a defined approval process.
Risk control has to work when things are moving fast.
We use drawdown triggers, exposure alerts, and abnormal behavior detection. If conditions break expectations, we reduce risk. If the environment becomes unstable, we pause.
Arbitrage is often described as low risk. In reality, it is low risk only when monitoring is relentless.
We track edge stability, latency sensitivity, venue reliability, and fill probability. If spreads compress or execution becomes inconsistent, we do not force it. We step back.
Good reporting is risk management.
Clients should understand what drove performance, what risks were taken, and where exposure sits. We focus on clarity. If you need a translator to understand the report, the report is not good enough.
Security is part of risk. Full stop.
We use access controls, encryption, and strict permissions. We also limit access internally based on role, because trust is not just about technology. It is about process.
This environment is designed for signal support and fast detection.
Where AI helps
Where guardrails matter
AI is a tool in the workflow. The rules and accountability sit with the team.
This environment is built for traders who want a traditional toolkit with clear execution.
Primary risks
Controls we focus on
CFDs can be effective when used responsibly. The risk comes from treating leverage casually.
This environment focuses on relative pricing opportunities and execution discipline.
Primary risks
Controls we focus on
Arbitrage is not “set and forget.” It is monitor, verify, and scale only when the edge is real.
This environment is designed for clients who want a more stable approach and prefer defined terms.
Primary risks
Controls we focus on
The priority here is straightforward communication. Clients should know exactly what they are choosing: the terms, the constraints, and the trade-offs.
Every investor has a different starting point. Let’s find yours—and build from there.