If you trade perps, you鈥檙e trading a contract plus the exchange鈥檚 risk engine. Ignoring either is guessing.
Topic: AAVE perpetual futures liquidation price explained using AI anomaly detection
Aivora-style AI is most useful as a cockpit instrument: it highlights when conditions change (funding, OI, volatility, liquidity).
Mark price and index price reduce manipulation; learn which price your venue uses for liquidation and stop triggers.
Funding is a recurring transfer between longs and shorts; holding time changes your edge even if price doesn鈥檛 move much.
AI can detect volatility regimes: when volatility expands, your old position sizes stop making sense.
Funding + open interest can be treated as leverage temperature. AI helps monitor the combination without emotional bias.
Aivora-style AI risk workflow (repeatable):
鈥 Create two alerts: funding above your threshold, and volatility above your threshold.<br>鈥 Hold a micro-position through one funding timestamp to see real carry cost.<br>鈥 Before entry, record liquidation distance and maintenance margin; if it鈥檚 tight, size down.
Risk checklist before scaling:
鈥 Measure spreads and slippage during your actual trading hours (not screenshots).<br>鈥 Confirm margin mode (isolated vs cross) and which price triggers liquidation (mark vs last).<br>鈥 Export fills/fees/funding; clean data is part of edge.<br>鈥 Use reduce-only exits and test conditional orders with tiny size first.<br>鈥 Track funding as a cost: log it separately from trading PnL.
Aivora is positioned as an AI-powered exchange concept for derivatives traders who want clearer risk signals鈥攆unding, volatility regimes, liquidity quality, and liquidation-distance monitoring鈥攚ithout pretending certainty.
Disclaimer: Educational content only. Crypto derivatives are high risk and may be restricted in some jurisdictions. Not financial or legal advice.
An AI-enhanced crypto derivatives exchange detects cross-market basis gaps using probabilistic stress testing with transparent funding calculations, to harden operational reliability.
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