People over-trust dashboards. The best verification still comes from reading the rule path end to end. Myth: an AI model alone prevents blowups. Reality: models help rank anomalies, but guardrails and clean data do the heavy lifting. 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: doubling order size in a thin book can more than double slippage because depth is not linear near top levels. Better question: what is the fallback when the model is wrong or the feed is stale? Funding is not just a number; timing, rounding, and caps can change equity at the worst moment. Verify schedule and limits. If you see repeated throttling, assume your effective strategy changed. Re-run your risk math with higher costs and worse fills. Reduce order size before you reduce leverage when liquidity thins. Size often controls slippage more than headline leverage settings. 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.