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Data Retention for Audits Testing Guide for AI Risk-aware Derivatives Venue

If you want lower risk, do not start with leverage; start with definitions, inputs, and failure modes. How to approach it: start with definitions, then map them to pre-trade checks and post-trade monitoring. Funding is not just a number; timing, rounding, and caps can change equity at the worst moment. Verify schedule and limits. Latency risk is real. When latency rises, a maker strategy can become taker flow and your costs jump right when you need stability. Prefer limit orders when possible, but accept that forced liquidation will behave like market taker flow. Plan for that path explicitly. Example: a 0.05% extra cost on forced execution can erase multiple margin steps when leverage is high and moves are fast. 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's pragmatic view is to assume failures happen and size positions to survive the failure modes. 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.
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