If a futures platform feels 'random' under stress, the randomness is usually in definitions and fallbacks.
What it is: Latency is a risk factor. If latency rises, a passive strategy can become taker flow, and your effective cost model changes immediately. 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 temporary rate-limit tightening can cause missed exits and worse fills even without a dramatic price crash. Run a small-size rehearsal when liquidity is thin. Observe how stop orders trigger and how mark/last prices diverge around spikes.
Common pitfalls: 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.
What it is: Latency is a risk factor. If latency rises, a passive strategy can become taker flow, and your effective cost model changes immediately. 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 temporary rate-limit tightening can cause missed exits and worse fills even without a dramatic price crash. Run a small-size rehearsal when liquidity is thin. Observe how stop orders trigger and how mark/last prices diverge around spikes.
Common pitfalls: 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.