Aivora AI-native exchange insights
Home Theo Hamilton Maintenance Margin Explained Explained for AI Risk-managed Perp Exchange

Maintenance Margin Explained Explained for AI Risk-managed Perp Exchange

AI can help rank anomalies, but it cannot replace clear rules you can audit.

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

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

How to verify: 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. Treat cross margin as a correlated portfolio. Correlations converge during stress, so diversification can vanish when you need it most.

Practical habit: Pitfall: trusting a single data source. One stale oracle feed can distort index and mark calculations if fallbacks are weak.

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.