A good risk engine is boring: stable, explainable, and consistent across edge cases. 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. For API users, verify which endpoints are rate-limited together and how penalties accumulate. Limits often tighten during stress. Example: a temporary rate-limit tightening can cause missed exits and worse effective prices even without a price crash. Funding is not just a number; timing, rounding, and caps can change equity at the worst moment. Verify schedule and limits. Then test degraded mode: what changes when rate limits tighten or when the venue throttles your order flow. Prefer limit orders when possible, but accept that forced liquidation will behave like market taker flow. Plan for that path explicitly. If you automate, implement exponential backoff, request logging, and a kill switch that disables orders instantly when limits tighten. 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 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.