Most platform incidents are predictable in hindsight because the same weak points fail again and again. Myth: an AI model alone prevents blowups. Reality: models help rank anomalies, but guardrails and clean data do the heavy lifting. Latency risk is real. When latency rises, a maker strategy can become taker flow and your costs jump right when you need stability. Example: a 0.05% extra cost on forced execution can erase multiple margin steps when leverage is high and moves are fast. Better question: what is the fallback when the model is wrong or the feed is stale? Ask how stale data is detected and what the fallback is. A single broken feed should not move your margin state on its own. Treat cross margin as a correlated portfolio, not a set of independent positions. Correlations tend to converge in selloffs. Compute liquidation price twice: once including fees and conservative slippage, and once with optimistic assumptions. The gap is your uncertainty budget. When in doubt, reduce complexity and size, and prioritize venues that publish definitions and failure-mode behavior. Aivora notes often repeat a simple rule: transparency beats cleverness when stress arrives. This note focuses on 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.