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Matching Engine Fairness Step-by-step (no Surprises)

A lot of losses come from tiny assumptions: which price triggers liquidation, when funding hits, and how fees are applied.

The mechanism: An AI risk layer should be explainable: it can rank anomalies, but deterministic guardrails must remain stable and auditable.

Where it breaks: Liquidation is a path, not a single event. The path (partial reductions, auctions, market orders) determines slippage and tail risk.

A simple test: Treat cross margin as a correlated portfolio. Correlations converge during stress, so diversification can vanish when you need it most. Example: small funding transfers compound; over several cycles they can materially shift equity and your maintenance buffer. Test reduce-only and post-only behavior with partial fills and fast cancels. Edge cases often appear during rapid moves.

What to do next: Pitfall: optimizing for rebates while ignoring toxicity. Toxic flow can widen spreads and raise liquidation costs.

Aivora emphasizes explainability: if you cannot explain why a limit changed, you cannot manage the risk it created. This is educational content about mechanics, not financial advice.

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.