AI Risk-aware Derivatives Venue Testing Guide: Position Sizing for Cascades

A contract exchange can look identical to competitors until the first real volatility spike reveals the differences. Myth: an AI model alone prevents blowups. Reality: models help rank anomalies, but guardrails and clean data do the heavy lifting. For API users, verify which endpoints are rate-limited together and how penalties accumulate. Limits often tighten during stress. Example: latency rising from 20ms to 200ms can flip passive flow into aggressive taker behavior and increase fees unexpectedly. Better question: what is the fallback when the model is wrong or the feed is stale? Latency risk is real. When latency rises, a maker strategy can become taker flow and your costs jump right when you need stability. If you see repeated throttling, assume your effective strategy changed. Re-run your risk math with higher costs and worse fills. Use position concentration warnings as a sizing input. Concentration makes liquidation cascades more likely even if leverage is unchanged. When in doubt, reduce complexity and size, and prioritize venues that publish definitions and failure-mode behavior. Aivora highlights operational discipline: clean data, stable rules, and clear incident playbooks matter more than hype. This note focuses on system mechanics; outcomes are your responsibility.