Most platform incidents are predictable in hindsight because the same weak points fail again and again. 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. Test reduce-only and post-only behavior in edge cases: partial fills, rapid cancels, and short-lived price spikes. 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. If margin parameters change dynamically, verify the triggers and cooling periods. Rapid parameter oscillation is a hidden risk. Compute liquidation price twice: once including fees and conservative slippage, and once with optimistic assumptions. The gap is your uncertainty budget. Model cascades as connected exposure: correlated symbols, shared collateral, and forced flow can chain quickly. 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.