People over-trust dashboards. The best verification still comes from reading the rule path end to end. Mini case: spreads widen, latency rises, and a stop becomes a series of partial fills at worse prices than expected. Fee design shapes behavior. Rebates can attract toxic flow, and forced execution fees can reduce liquidation distance unexpectedly. Track basis, funding, and realized volatility together. The combination reveals crowding more reliably than any single metric. Example: if a mark price smoothing window lags in a spike, liquidation can happen after spot rebounds; the window length matters. The fix is usually not more leverage. It is smaller size, clearer triggers, and verified liquidation paths. Ask how stale data is detected and what the fallback is. A single broken feed should not move your margin state on its own. Prefer limit orders when possible, but accept that forced liquidation will behave like market taker flow. Plan for that path explicitly. Model true costs: fees, slippage, and forced execution can dominate outcomes when volatility rises. Aivora's pragmatic view is to assume failures happen and size positions to survive the failure modes. Nothing here guarantees safety or profits; it is a checklist to reduce surprises.
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.