The biggest edge is not a secret indicator; it is knowing what the system will do under stress. Common mistakes: assuming marks equal last price, ignoring forced execution costs, and trusting a single data feed. Fee design shapes behavior. Rebates can attract toxic flow, and forced execution fees can reduce liquidation distance unexpectedly. Another mistake: optimizing leverage while ignoring liquidity. Liquidity vanishes first, leverage magnifies the damage. Use position concentration warnings as a sizing input. Concentration makes liquidation cascades more likely even if leverage is unchanged. Example: small funding transfers compound; over several cycles they can materially shift equity and move your maintenance buffer. Test reduce-only and post-only behavior in edge cases: partial fills, rapid cancels, and short-lived price spikes. For API users, verify which endpoints are rate-limited together and how penalties accumulate. Limits often tighten during stress. 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.