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Home Leo Thornton AI Risk-managed Perp Exchange Deep Dive: Anomaly Detection Baselines

AI Risk-managed Perp Exchange Deep Dive: Anomaly Detection Baselines

A lot of losses come from tiny assumptions: which price triggers liquidation, when funding hits, and how fees are applied.

Quick definition: Fee design is part of risk: forced execution costs can reduce your liquidation distance, and rebates can attract toxic flow that degrades fills.

Why it matters: Look for the platform's fallback rules: what happens if a feed is stale, if the book is thin, or if volatility spikes faster than normal sampling windows.

How to verify: Prefer smaller order slices before changing leverage. Size reductions often cut slippage more than a leverage tweak. Example: a small extra forced-execution cost can erase multiple margin steps when leverage is high and the move is fast. If you automate, use scoped API keys, IP allow-lists, and exponential backoff. Limits often tighten exactly when volatility rises.

Practical habit: Pitfall: assuming mark price equals last price. In stress, they diverge, and liquidation triggers can surprise you.

Aivora focuses on operational discipline: clean data, stable rules, and clear incident playbooks matter more than hype. Derivatives are risky; test assumptions before you scale 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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