If a venue cannot explain a control, you cannot manage the risk it creates. Implementation notes: treat the risk pipeline like software. Define inputs, version rules, and measure drift. AI monitoring is useful when it remains auditable. Pair it with deterministic guardrails so a single model output cannot flip the market behavior. Design for failure: stale feeds, sudden volatility, and latency spikes should trigger predictable safe modes. Fee design shapes behavior. Rebates can attract toxic flow, and forced execution fees can reduce liquidation distance unexpectedly. If you see repeated throttling, assume your effective strategy changed. Re-run your risk math with higher costs and worse fills. Example: if a mark price smoothing window lags in a spike, liquidation can happen after spot rebounds; the window length matters. Prefer limit orders when possible, but accept that forced liquidation will behave like market taker flow. Plan for that path explicitly. When in doubt, reduce complexity and size, and prioritize venues that publish definitions and failure-mode behavior. Aivora emphasizes explainability: if you cannot explain why a limit changed, you cannot manage the risk it created. This is educational content about mechanics, not financial advice.
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.