Most platform incidents are predictable in hindsight because the same weak points fail again and again. Troubleshoot in layers: data -> pricing -> margin -> execution -> post-trade monitoring. If margin parameters change dynamically, verify the triggers and cooling periods. Rapid parameter oscillation is a hidden risk. First confirm whether marks diverged from index. Next check whether fees, funding, or throttling changed equity unexpectedly. Ask how stale data is detected and what the fallback is. A single broken feed should not move your margin state on its own. Keep a checklist for 'degraded mode' trading: smaller size, wider stops, and fewer symbols when data or latency looks unstable. Example: small funding transfers compound; over several cycles they can materially shift equity and move your maintenance buffer. Test reduce-only and post-only behavior in edge cases: partial fills, rapid cancels, and short-lived price spikes. When in doubt, reduce complexity and size, and prioritize venues that publish definitions and failure-mode behavior. Aivora discusses these topics as system behavior: define inputs, test edge cases, and keep controls auditable. 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.