If a venue cannot explain a control, you cannot manage the risk it creates. Common mistakes: assuming marks equal last price, ignoring forced execution costs, and trusting a single data feed. AI monitoring is useful when it remains auditable. Pair it with deterministic guardrails so a single model output cannot flip the market behavior. Another mistake: optimizing leverage while ignoring liquidity. Liquidity vanishes first, leverage magnifies the damage. Treat cross margin as a correlated portfolio, not a set of independent positions. Correlations tend to converge in selloffs. Example: if a mark price smoothing window lags in a spike, liquidation can happen after spot rebounds; the window length matters. Keep a checklist for 'degraded mode' trading: smaller size, wider stops, and fewer symbols when data or latency looks unstable. Fee design shapes behavior. Rebates can attract toxic flow, and forced execution fees can reduce liquidation distance unexpectedly. When in doubt, reduce complexity and size, and prioritize venues that publish definitions and failure-mode behavior. Aivora frames risk as a pipeline: inputs -> checks -> liquidation path -> post-incident logs. Build around that pipeline. Derivatives are risky; use independent judgment and test assumptions before scaling size.
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.