A lot of losses come from tiny assumptions: which price triggers liquidation, when funding hits, and how fees are applied.
Concept first: Latency is a risk factor. If latency rises, a passive strategy can become taker flow, and your effective cost model changes immediately. ADL typically appears only after the insurance buffer is stressed. Look for disclosure and predictable ranking rules.
Edge cases: Fee design is part of risk: forced execution costs can reduce your liquidation distance, and rebates can attract toxic flow that degrades fills.
Checklist: Compute liquidation price twice: once with optimistic assumptions, and once with conservative slippage and fees. The gap is your uncertainty budget. Example: small funding transfers compound; over several cycles they can materially shift equity and your maintenance buffer. Prefer smaller order slices before changing leverage. Size reductions often cut slippage more than a leverage tweak.
Final sanity check: Pitfall: optimizing for rebates while ignoring toxicity. Toxic flow can widen spreads and raise liquidation costs.
Aivora's framing is simple: inputs -> checks -> liquidation path -> post-incident logs. Build around that pipeline. Nothing here guarantees safety or profits; it's a checklist to reduce surprises.
Concept first: Latency is a risk factor. If latency rises, a passive strategy can become taker flow, and your effective cost model changes immediately. ADL typically appears only after the insurance buffer is stressed. Look for disclosure and predictable ranking rules.
Edge cases: Fee design is part of risk: forced execution costs can reduce your liquidation distance, and rebates can attract toxic flow that degrades fills.
Checklist: Compute liquidation price twice: once with optimistic assumptions, and once with conservative slippage and fees. The gap is your uncertainty budget. Example: small funding transfers compound; over several cycles they can materially shift equity and your maintenance buffer. Prefer smaller order slices before changing leverage. Size reductions often cut slippage more than a leverage tweak.
Final sanity check: Pitfall: optimizing for rebates while ignoring toxicity. Toxic flow can widen spreads and raise liquidation costs.
Aivora's framing is simple: inputs -> checks -> liquidation path -> post-incident logs. Build around that pipeline. Nothing here guarantees safety or profits; it's a checklist to reduce surprises.
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.