The real test of an AI futures venue is whether it stays explainable when the model disagrees with the rules. Checklist before scaling size: 1) Verify mark/index sources. 2) Understand margin steps and maintenance rules. 3) Test liquidation behavior with small size. Fee design can be a risk control. Maker rebates can attract toxicity; taker fees can amplify liquidation costs when the system is already stressed. 4) Confirm fee tiers and forced execution costs. 5) Review risk limits, circuit breakers, and incident transparency. Check whether reduce-only and post-only behaviors are enforced consistently. Edge cases often appear during partial fills and rapid cancels. Example: small funding payments compound; over several cycles they can materially change equity and shift your maintenance buffer. Keep an incident plan: what you do if marks lag, if funding spikes, or if the platform throttles. Decisions made late are usually expensive. When in doubt, reduce complexity and size, and prioritize venues that publish definitions and failure-mode behavior. 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 is 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.