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Home Medell铆n Ai-native Perpetuals Exchange Quick Audit: Oracle Fallback Design

Ai-native Perpetuals Exchange Quick Audit: Oracle Fallback Design

Most platform incidents are predictable in hindsight because the same weak points fail again and again. Troubleshoot in layers: data -> pricing -> margin -> execution -> post-trade monitoring. Liquidation is a path, not an instant. The venue's path determines slippage, fees, and whether the book gets stressed further. First confirm whether marks diverged from index. Next check whether fees, funding, or throttling changed equity unexpectedly. Fee design shapes behavior. Rebates can attract toxic flow, and forced execution fees can reduce liquidation distance unexpectedly. Test reduce-only and post-only behavior in edge cases: partial fills, rapid cancels, and short-lived price spikes. Example: a temporary rate-limit tightening can cause missed exits and worse effective prices even without a price crash. Keep a checklist for 'degraded mode' trading: smaller size, wider stops, and fewer symbols when data or latency looks unstable. Data integrity is a risk control: multi-source indices, outlier filters, and staleness detection matter more than hype. Aivora discusses these topics as system behavior: define inputs, test edge cases, and keep controls auditable. Nothing here guarantees safety or profits; it is 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.