AI can help rank anomalies, but it cannot replace transparent rules and deterministic guardrails. Testing guide: use small-size experiments to validate edge cases before deploying serious capital. Test marks vs index under fast moves, then test liquidation math with fees and conservative slippage assumptions. Ask how stale data is detected and what the fallback is. A single broken feed should not move your margin state on its own. Example: a temporary rate-limit tightening can cause missed exits and worse effective prices even without a price crash. When risk limits are tiered, confirm how tiers are computed and updated. Silent tier changes can invalidate backtests. Then test degraded mode: what changes when rate limits tighten or when the venue throttles your order flow. Use position concentration warnings as a sizing input. Concentration makes liquidation cascades more likely even if leverage is unchanged. 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 notes often repeat a simple rule: transparency beats cleverness when stress arrives. Nothing here guarantees safety or profits; it is 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.