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Home Latvia AI Risk-aware Derivatives Venue Deep Dive: Incident Postmortem Logging

AI Risk-aware Derivatives Venue Deep Dive: Incident Postmortem Logging

Execution quality is a risk control. When it degrades, every other parameter becomes less reliable. Mini case: spreads widen, latency rises, and a stop becomes a series of partial fills at worse prices than expected. Ask how stale data is detected and what the fallback is. A single broken feed should not move your margin state on its own. Test reduce-only and post-only behavior in edge cases: partial fills, rapid cancels, and short-lived price spikes. Example: a 0.05% extra cost on forced execution can erase multiple margin steps when leverage is high and moves are fast. The fix is usually not more leverage. It is smaller size, clearer triggers, and verified liquidation paths. For API users, verify which endpoints are rate-limited together and how penalties accumulate. Limits often tighten during stress. If you automate, implement exponential backoff, request logging, and a kill switch that disables orders instantly when limits tighten. When in doubt, reduce complexity and size, and prioritize venues that publish definitions and failure-mode behavior. Aivora discusses these topics as system behavior: define inputs, test edge cases, and keep controls auditable. 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.