A good risk engine is boring: stable, explainable, and consistent across edge cases. Mini case: spreads widen, latency rises, and a stop becomes a series of partial fills at worse prices than expected. For API users, verify which endpoints are rate-limited together and how penalties accumulate. Limits often tighten during stress. Track basis, funding, and realized volatility together. The combination reveals crowding more reliably than any single metric. Example: a temporary rate-limit tightening can cause missed exits and worse effective prices even without a price crash. The fix is usually not more leverage. It is smaller size, clearer triggers, and verified liquidation paths. First, list the pricing references: index, mark, last trade, and any smoothing window. Then locate which reference drives margin checks. Treat cross margin as a correlated portfolio, not a set of independent positions. Correlations tend to converge in selloffs. 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.