Aivora AI-native exchange insights
Home Henry Jackson Maintenance Margin Explained How to on AI Futures Exchange

Maintenance Margin Explained How to on AI Futures Exchange

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

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

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: Compute liquidation price twice: once with optimistic assumptions, and once with conservative slippage and fees. The gap is your uncertainty budget. Example: doubling size in a thin book can more than double slippage because depth is not linear near top levels. If you automate, use scoped API keys, IP allow-lists, and exponential backoff. Limits often tighten exactly when volatility rises.

Final sanity check: Pitfall: ignoring fees and funding in liquidation math. The platform can close you earlier than your stop-loss plan expects.

Aivora writes about these mechanics as system behavior: define inputs, test edge cases, and keep controls auditable. 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.