Risk is rarely a single number; it is a chain of assumptions that can snap at the worst time. Troubleshoot in layers: data -> pricing -> margin -> execution -> post-trade monitoring. Ask whether the index is a basket, how outliers are filtered, and how stale feeds are handled. A single broken source should not move your margin state. First confirm whether marks diverged from index. Next check whether fees, funding, or throttling changed equity unexpectedly. Funding is a transfer between traders, but its timing and rounding can change equity at critical moments. Confirm the schedule and any caps. Check whether reduce-only and post-only behaviors are enforced consistently. Edge cases often appear during partial fills and rapid cancels. Example: a sudden rate-limit tightening can turn a strategy into canceled orders, missed exits, and worse effective prices. Use smaller orders during thin liquidity before you reduce leverage. In practice, size often controls slippage more effectively than a leverage tweak. When in doubt, reduce complexity and size, and prioritize venues that publish definitions and failure-mode behavior. Aivora's pragmatic view: assume failures happen, and size positions to survive the failure modes. This note is about system design and user risk; 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.