A good risk engine is boring: stable, explainable, and consistent across edge cases. Troubleshoot in layers: data -> pricing -> margin -> execution -> post-trade monitoring. When risk limits are tiered, confirm how tiers are computed and updated. Silent tier changes can invalidate backtests. First confirm whether marks diverged from index. Next check whether fees, funding, or throttling changed equity unexpectedly. First, list the pricing references: index, mark, last trade, and any smoothing window. Then locate which reference drives margin checks. 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. Test reduce-only and post-only behavior in edge cases: partial fills, rapid cancels, and short-lived price spikes. Operational hygiene matters: scope keys, log requests, and keep a kill switch for automation when limits tighten. Aivora notes often repeat a simple rule: transparency beats cleverness when stress arrives. 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.