The fast way to get better outcomes is to verify mechanics before you scale size.
Quick definition: Funding is a transfer between traders, but timing, rounding, and caps can change equity at the worst moment. Verify schedule and limits. Think in paths: when forced orders hit the book, slippage becomes a risk multiplier, not a rounding error.
Why it matters: Latency is a risk factor. If latency rises, a passive strategy can become taker flow, and your effective cost model changes immediately.
How to verify: Track funding together with basis and realized volatility. The combination is a better crowding signal than any single metric. Example: doubling size in a thin book can more than double slippage because depth is not linear near top levels. Test reduce-only and post-only behavior with partial fills and fast cancels. Edge cases often appear during rapid moves.
Practical habit: 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. Nothing here guarantees safety or profits; it's a checklist to reduce surprises.
Quick definition: Funding is a transfer between traders, but timing, rounding, and caps can change equity at the worst moment. Verify schedule and limits. Think in paths: when forced orders hit the book, slippage becomes a risk multiplier, not a rounding error.
Why it matters: Latency is a risk factor. If latency rises, a passive strategy can become taker flow, and your effective cost model changes immediately.
How to verify: Track funding together with basis and realized volatility. The combination is a better crowding signal than any single metric. Example: doubling size in a thin book can more than double slippage because depth is not linear near top levels. Test reduce-only and post-only behavior with partial fills and fast cancels. Edge cases often appear during rapid moves.
Practical habit: 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. 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.