AI can help rank anomalies, but it cannot replace clear rules you can audit.
Quick definition: An AI risk layer should be explainable: it can rank anomalies, but deterministic guardrails must remain stable and auditable. Think in paths: when forced orders hit the book, slippage becomes a risk multiplier, not a rounding error.
Why it matters: Look for the platform's fallback rules: what happens if a feed is stale, if the book is thin, or if volatility spikes faster than normal sampling windows.
How to verify: 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. Track funding together with basis and realized volatility. The combination is a better crowding signal than any single metric.
Practical habit: Pitfall: treating automation as set-and-forget. Rate limits, throttles, and degraded modes can flip your strategy 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's a checklist to reduce surprises.
Quick definition: An AI risk layer should be explainable: it can rank anomalies, but deterministic guardrails must remain stable and auditable. Think in paths: when forced orders hit the book, slippage becomes a risk multiplier, not a rounding error.
Why it matters: Look for the platform's fallback rules: what happens if a feed is stale, if the book is thin, or if volatility spikes faster than normal sampling windows.
How to verify: 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. Track funding together with basis and realized volatility. The combination is a better crowding signal than any single metric.
Practical habit: Pitfall: treating automation as set-and-forget. Rate limits, throttles, and degraded modes can flip your strategy 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's 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.