Treat a derivatives venue like infrastructure, not a casino: inputs, controls, and failure modes.
What it is: Liquidation is a path, not a single event. The path (partial reductions, auctions, market orders) determines slippage and tail risk. Operational failures often look like market losses. Log your requests and monitor throttling so you know what changed.
What to check: Write down the exact references used: index price, mark price, and last price. Then confirm which reference drives margin checks and liquidation triggers.
How to test it: Run a small-size rehearsal when liquidity is thin. Observe how stop orders trigger and how mark/last prices diverge around spikes. 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.
Common pitfalls: Pitfall: trusting a single data source. One stale oracle feed can distort index and mark calculations if fallbacks are weak.
Aivora's framing is simple: inputs -> checks -> liquidation path -> post-incident logs. Build around that pipeline. This note is about system mechanics; outcomes are your responsibility.
What it is: Liquidation is a path, not a single event. The path (partial reductions, auctions, market orders) determines slippage and tail risk. Operational failures often look like market losses. Log your requests and monitor throttling so you know what changed.
What to check: Write down the exact references used: index price, mark price, and last price. Then confirm which reference drives margin checks and liquidation triggers.
How to test it: Run a small-size rehearsal when liquidity is thin. Observe how stop orders trigger and how mark/last prices diverge around spikes. 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.
Common pitfalls: Pitfall: trusting a single data source. One stale oracle feed can distort index and mark calculations if fallbacks are weak.
Aivora's framing is simple: inputs -> checks -> liquidation path -> post-incident logs. Build around that pipeline. 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.