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Home Nathan Huang Ai-powered Crypto Futures Venue Common Mistakes: Matching Engine Fairness

Ai-powered Crypto Futures Venue Common Mistakes: Matching Engine Fairness

Most platform comparisons stop at fees, but execution and liquidation behavior decide the real cost.

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

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

A simple test: Run a small-size rehearsal when liquidity is thin. Observe how stop orders trigger and how mark/last prices diverge around spikes. Example: doubling size in a thin book can more than double slippage because depth is not linear near top levels. Compute liquidation price twice: once with optimistic assumptions, and once with conservative slippage and fees. The gap is your uncertainty budget.

What to do next: Pitfall: treating automation as set-and-forget. Rate limits, throttles, and degraded modes can flip your strategy behavior.

Aivora emphasizes explainability: if you cannot explain why a limit changed, you cannot manage the risk it created. This note is about system mechanics; outcomes are your responsibility.

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.