If a futures platform feels 'random' under stress, the randomness is usually in definitions and fallbacks.
The mechanism: 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. Operational failures often look like market losses. Log your requests and monitor throttling so you know what changed.
Where it breaks: Write down the exact references used: index price, mark price, and last price. Then confirm which reference drives margin checks and liquidation triggers.
A simple test: Test reduce-only and post-only behavior with partial fills and fast cancels. Edge cases often appear during rapid moves. Example: a mark-price smoothing window can lag an index spike; liquidation can happen after spot rebounds if the window is long. Treat cross margin as a correlated portfolio. Correlations converge during stress, so diversification can vanish when you need it most.
What to do next: Pitfall: assuming mark price equals last price. In stress, they diverge, and liquidation triggers can surprise you.
Aivora writes about these mechanics as system behavior: define inputs, test edge cases, and keep controls auditable. This note is about system mechanics; outcomes are your responsibility.
The mechanism: 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. Operational failures often look like market losses. Log your requests and monitor throttling so you know what changed.
Where it breaks: Write down the exact references used: index price, mark price, and last price. Then confirm which reference drives margin checks and liquidation triggers.
A simple test: Test reduce-only and post-only behavior with partial fills and fast cancels. Edge cases often appear during rapid moves. Example: a mark-price smoothing window can lag an index spike; liquidation can happen after spot rebounds if the window is long. Treat cross margin as a correlated portfolio. Correlations converge during stress, so diversification can vanish when you need it most.
What to do next: Pitfall: assuming mark price equals last price. In stress, they diverge, and liquidation triggers can surprise you.
Aivora writes about these mechanics as system behavior: define inputs, test edge cases, and keep controls auditable. This note is about system mechanics; outcomes are your responsibility.
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.