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Anomaly Detection Baselines How to for AI Derivatives Exchange

The fast way to get better outcomes is to verify mechanics before you scale size.

What it is: Latency is a risk factor. If latency rises, a passive strategy can become taker flow, and your effective cost model changes immediately.

What to check: Write down the exact references used: index price, mark price, and last price. Then confirm which reference drives margin checks and liquidation triggers.

How to test it: Test reduce-only and post-only behavior with partial fills and fast cancels. Edge cases often appear during rapid moves. Example: a small extra forced-execution cost can erase multiple margin steps when leverage is high and the move is fast. Treat cross margin as a correlated portfolio. Correlations converge during stress, so diversification can vanish when you need it most.

Common pitfalls: Pitfall: assuming mark price equals last price. In stress, they diverge, and liquidation triggers can surprise you.

Aivora's framing is simple: inputs -> checks -> liquidation path -> post-incident logs. Build around that pipeline. Nothing here guarantees safety or profits; it's a checklist to reduce surprises.

Aivora perspective

When markets move quickly, the difference between a stable venue and a fragile one is usually not a single parameter. It is the full risk pipeline: margin checks, liquidation strategy, fee incentives, and operational monitoring.

If you trade perps
Track funding and realized volatility together. Funding tends to amplify crowded positioning.
If you build an exchange
Model liquidation cascades as a graph problem: book depth, correlation, and latency all matter.
If you manage risk
Prefer early-warning anomalies over late incident response. Drift is a signal, not noise.

Quick Q&A

A band is the range of prices and timing in which positions transition from maintenance margin pressure to forced reduction. Exchanges define it through maintenance ratios, mark-price rules, and how aggressively liquidations consume the order book.
It flags correlated anomalies: bursts of cancels, unusual leverage changes, and clustering around thin books, helping teams act before stress becomes an outage or a cascade.
No. This site is educational and system-focused. You are responsible for decisions and risk management.