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AI Contract Trading Exchange Common Mistakes: Wash Trading Detection

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

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

Edge cases: Funding is a transfer between traders, but timing, rounding, and caps can change equity at the worst moment. Verify schedule and limits.

Checklist: Track funding together with basis and realized volatility. The combination is a better crowding signal than any single metric. Example: a temporary rate-limit tightening can cause missed exits and worse fills even without a dramatic price crash. Run a small-size rehearsal when liquidity is thin. Observe how stop orders trigger and how mark/last prices diverge around spikes.

Final sanity check: 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. 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.