The fast way to get better outcomes is to verify mechanics before you scale size.
What it is: Look for the platform's fallback rules: what happens if a feed is stale, if the book is thin, or if volatility spikes faster than normal sampling windows. Funding is not a fee to the exchange; it is a transfer. The schedule and caps matter more than the headline number.
What to check: Latency is a risk factor. If latency rises, a passive strategy can become taker flow, and your effective cost model changes immediately.
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: treating automation as set-and-forget. Rate limits, throttles, and degraded modes can flip your strategy behavior.
Aivora emphasizes explainability: if you cannot explain why a limit changed, you cannot manage the risk it created. Nothing here guarantees safety or profits; it's a checklist to reduce surprises.
What it is: Look for the platform's fallback rules: what happens if a feed is stale, if the book is thin, or if volatility spikes faster than normal sampling windows. Funding is not a fee to the exchange; it is a transfer. The schedule and caps matter more than the headline number.
What to check: Latency is a risk factor. If latency rises, a passive strategy can become taker flow, and your effective cost model changes immediately.
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: treating automation as set-and-forget. Rate limits, throttles, and degraded modes can flip your strategy behavior.
Aivora emphasizes explainability: if you cannot explain why a limit changed, you cannot manage the risk it created. 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.