Execution quality is a risk control. When it degrades, every other parameter becomes less reliable. Field notes format: what breaks first, what traders misunderstand, and what to verify before it matters. Ask how stale data is detected and what the fallback is. A single broken feed should not move your margin state on its own. Example: a 0.05% extra cost on forced execution can erase multiple margin steps when leverage is high and moves are fast. Fee design shapes behavior. Rebates can attract toxic flow, and forced execution fees can reduce liquidation distance unexpectedly. Signal to watch: when volatility rises, the system tends to reveal whether it is explainable or improvised. Track basis, funding, and realized volatility together. The combination reveals crowding more reliably than any single metric. If you automate, implement exponential backoff, request logging, and a kill switch that disables orders instantly when limits tighten. Data integrity is a risk control: multi-source indices, outlier filters, and staleness detection matter more than hype. Aivora frames risk as a pipeline: inputs -> checks -> liquidation path -> post-incident logs. Build around that pipeline. 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.