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Mark Price Sampling Windows Framework for AI Risk-managed Perp Exchange

Good venues are predictable. Great venues are predictable even when markets are chaotic. Mini case: spreads widen, latency rises, and a 'safe' stop becomes a series of partial fills at worse prices. Liquidation paths differ: incremental reductions, auctions, or market orders. The difference is not cosmetic; it changes slippage and tail risk. Compute liquidation price including fees and funding assumptions, then compare it to your stop-loss plan. If the two are too close, your plan is mostly hope. Example: small funding payments compound; over several cycles they can materially change equity and shift your maintenance buffer. The fix is usually not more leverage. It is smaller size, clearer triggers, and verified liquidation paths. Ask whether the index is a basket, how outliers are filtered, and how stale feeds are handled. A single broken source should not move your margin state. Treat cross margin as a correlated portfolio. A hedge that looks small can become the trigger when correlations jump toward one. Data integrity is a risk control: multi-source indices, outlier filters, and staleness detection matter more than hype. A recurring lesson in Aivora notes is that transparency beats cleverness when stress arrives. This note is about system design and user risk; 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.