Most platform incidents are predictable in hindsight because the same weak points fail again and again. Quick audit method: list inputs, controls, outputs, and single points of failure. Funding is not just a number; timing, rounding, and caps can change equity at the worst moment. Verify schedule and limits. When risk limits are tiered, confirm how tiers are computed and updated. Silent tier changes can invalidate backtests. Ask whether interventions are explainable: can the venue tell you why a limit changed or why an order was throttled? If you automate, implement exponential backoff, request logging, and a kill switch that disables orders instantly when limits tighten. Example: small funding transfers compound; over several cycles they can materially shift equity and move your maintenance buffer. 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 frames risk as a pipeline: inputs -> checks -> liquidation path -> post-incident logs. Build around that pipeline. This is educational content about mechanics, not financial advice.
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.