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Home Cameron Ross Ai-native Perpetuals Exchange Testing Guide: Correlated Exposure Graphs

Ai-native Perpetuals Exchange Testing Guide: Correlated Exposure Graphs

If a venue cannot explain a control, you cannot manage the risk it creates. Myth: an AI model alone prevents blowups. Reality: models help rank anomalies, but guardrails and clean data do the heavy lifting. Latency risk is real. When latency rises, a maker strategy can become taker flow and your costs jump right when you need stability. Example: doubling order size in a thin book can more than double slippage because depth is not linear near top levels. Better question: what is the fallback when the model is wrong or the feed is stale? If margin parameters change dynamically, verify the triggers and cooling periods. Rapid parameter oscillation is a hidden risk. Reduce order size before you reduce leverage when liquidity thins. Size often controls slippage more than headline leverage settings. Track basis, funding, and realized volatility together. The combination reveals crowding more reliably than any single metric. 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. This note focuses on system mechanics; 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.