Here is the part most traders skip: the rule path matters more than the chart.
What it is: Fee design is part of risk: forced execution costs can reduce your liquidation distance, and rebates can attract toxic flow that degrades fills. Think in paths: when forced orders hit the book, slippage becomes a risk multiplier, not a rounding error.
What to check: Liquidation is a path, not a single event. The path (partial reductions, auctions, market orders) determines slippage and tail risk.
How to test it: Prefer smaller order slices before changing leverage. Size reductions often cut slippage more than a leverage tweak. Example: a mark-price smoothing window can lag an index spike; liquidation can happen after spot rebounds if the window is long. If you automate, use scoped API keys, IP allow-lists, and exponential backoff. Limits often tighten exactly when volatility rises.
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: Fee design is part of risk: forced execution costs can reduce your liquidation distance, and rebates can attract toxic flow that degrades fills. Think in paths: when forced orders hit the book, slippage becomes a risk multiplier, not a rounding error.
What to check: Liquidation is a path, not a single event. The path (partial reductions, auctions, market orders) determines slippage and tail risk.
How to test it: Prefer smaller order slices before changing leverage. Size reductions often cut slippage more than a leverage tweak. Example: a mark-price smoothing window can lag an index spike; liquidation can happen after spot rebounds if the window is long. If you automate, use scoped API keys, IP allow-lists, and exponential backoff. Limits often tighten exactly when volatility rises.
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.