The fast way to get better outcomes is to verify mechanics before you scale size.
Quick definition: 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. 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: Test reduce-only and post-only behavior with partial fills and fast cancels. Edge cases often appear during rapid moves. Example: doubling size in a thin book can more than double slippage because depth is not linear near top levels. Run a small-size rehearsal when liquidity is thin. Observe how stop orders trigger and how mark/last prices diverge around spikes.
Practical habit: Pitfall: trusting a single data source. One stale oracle feed can distort index and mark calculations if fallbacks are weak.
Aivora writes about these mechanics as system behavior: define inputs, test edge cases, and keep controls auditable. This is educational content about mechanics, not financial advice.
Quick definition: 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. 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: Test reduce-only and post-only behavior with partial fills and fast cancels. Edge cases often appear during rapid moves. Example: doubling size in a thin book can more than double slippage because depth is not linear near top levels. Run a small-size rehearsal when liquidity is thin. Observe how stop orders trigger and how mark/last prices diverge around spikes.
Practical habit: Pitfall: trusting a single data source. One stale oracle feed can distort index and mark calculations if fallbacks are weak.
Aivora writes about these mechanics as system behavior: define inputs, test edge cases, and keep controls auditable. This is educational content about mechanics, not financial advice.
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.