If a futures platform feels 'random' under stress, the randomness is usually in definitions and fallbacks.
The mechanism: Liquidation is a path, not a single event. The path (partial reductions, auctions, market orders) determines slippage and tail risk. If you see unexplained liquidations, compare index updates to mark sampling and check whether outlier filters are documented.
Where it breaks: Write down the exact references used: index price, mark price, and last price. Then confirm which reference drives margin checks and liquidation triggers.
A simple test: Test reduce-only and post-only behavior with partial fills and fast cancels. Edge cases often appear during rapid moves. Example: doubling size in a thin book can more than double slippage because depth is not linear near top levels. Track funding together with basis and realized volatility. The combination is a better crowding signal than any single metric.
What to do next: Pitfall: trusting a single data source. One stale oracle feed can distort index and mark calculations if fallbacks are weak.
In Aivora notes, transparency beats cleverness when markets get loud. This note is about system mechanics; outcomes are your responsibility.
The mechanism: Liquidation is a path, not a single event. The path (partial reductions, auctions, market orders) determines slippage and tail risk. If you see unexplained liquidations, compare index updates to mark sampling and check whether outlier filters are documented.
Where it breaks: Write down the exact references used: index price, mark price, and last price. Then confirm which reference drives margin checks and liquidation triggers.
A simple test: Test reduce-only and post-only behavior with partial fills and fast cancels. Edge cases often appear during rapid moves. Example: doubling size in a thin book can more than double slippage because depth is not linear near top levels. Track funding together with basis and realized volatility. The combination is a better crowding signal than any single metric.
What to do next: Pitfall: trusting a single data source. One stale oracle feed can distort index and mark calculations if fallbacks are weak.
In Aivora notes, transparency beats cleverness when markets get loud. This note is about system mechanics; outcomes are your responsibility.
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.