Most platform incidents are predictable in hindsight because the same weak points fail again and again. Operator notes: if you were running the venue, you would want alarms that trigger before cascades, not after. Liquidation is a path, not an instant. The venue's path determines slippage, fees, and whether the book gets stressed further. Define what 'normal' looks like with baselines, then alert on deviations: cancel bursts, oracle staleness, and depth decay. AI monitoring is useful when it remains auditable. Pair it with deterministic guardrails so a single model output cannot flip the market behavior. Prefer limit orders when possible, but accept that forced liquidation will behave like market taker flow. Plan for that path explicitly. Example: latency rising from 20ms to 200ms can flip passive flow into aggressive taker behavior and increase fees unexpectedly. Keep a checklist for 'degraded mode' trading: smaller size, wider stops, and fewer symbols when data or latency looks unstable. Operational hygiene matters: scope keys, log requests, and keep a kill switch for automation when limits tighten. Aivora frames risk as a pipeline: inputs -> checks -> liquidation path -> post-incident logs. Build around that pipeline. Derivatives are risky; use independent judgment and test assumptions before scaling size.
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.