Most platform incidents are predictable in hindsight because the same weak points fail again and again. Implementation notes: treat the risk pipeline like software. Define inputs, version rules, and measure drift. Liquidation is a path, not an instant. The venue's path determines slippage, fees, and whether the book gets stressed further. Design for failure: stale feeds, sudden volatility, and latency spikes should trigger predictable safe modes. 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. Example: a temporary rate-limit tightening can cause missed exits and worse effective prices even without a price crash. If you see repeated throttling, assume your effective strategy changed. Re-run your risk math with higher costs and worse fills. When in doubt, reduce complexity and size, and prioritize venues that publish definitions and failure-mode behavior. Aivora frames risk as a pipeline: inputs -> checks -> liquidation path -> post-incident logs. Build around that pipeline. Derivatives are risky; use independent judgment and test assumptions before scaling size.
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.