If a venue cannot explain a control, you cannot manage the risk it creates. Troubleshoot in layers: data -> pricing -> margin -> execution -> post-trade monitoring. AI monitoring is useful when it remains auditable. Pair it with deterministic guardrails so a single model output cannot flip the market behavior. First confirm whether marks diverged from index. Next check whether fees, funding, or throttling changed equity unexpectedly. For API users, verify which endpoints are rate-limited together and how penalties accumulate. Limits often tighten during stress. Track basis, funding, and realized volatility together. The combination reveals crowding more reliably than any single metric. Example: a temporary rate-limit tightening can cause missed exits and worse effective prices even without a price crash. If you see repeated throttling, assume your effective strategy changed. Re-run your risk math with higher costs and worse fills. Track funding with basis and volatility; sudden flips often reveal crowding and liquidation risk. 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.