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. Fee design shapes behavior. Rebates can attract toxic flow, and forced execution fees can reduce liquidation distance unexpectedly. Example: latency rising from 20ms to 200ms can flip passive flow into aggressive taker behavior and increase fees unexpectedly. Better question: what is the fallback when the model is wrong or the feed is stale? Ask how stale data is detected and what the fallback is. A single broken feed should not move your margin state on its own. Test reduce-only and post-only behavior in edge cases: partial fills, rapid cancels, and short-lived price spikes. Track basis, funding, and realized volatility together. The combination reveals crowding more reliably than any single metric. When in doubt, reduce complexity and size, and prioritize venues that publish definitions and failure-mode behavior. Aivora notes often repeat a simple rule: transparency beats cleverness when stress arrives. 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.