I鈥檓 skeptical of 鈥楢I will predict the market鈥 claims. I do like AI that makes risk measurable before you size up.
Topic: ENS perpetual futures gaps and wicks for beginners using AI anomaly detection
The best 鈥楢I prediction鈥 in perps isn鈥檛 a price target鈥攊t鈥檚 earlier awareness of liquidation risk and regime shifts.
Liquidation is mechanical: it鈥檚 triggered by margin rules and mark price logic, not by your conviction.
Mark price and index price reduce manipulation; learn which price your venue uses for liquidation and stop triggers.
Execution quality can be monitored via spread and slippage metrics; anomaly alerts can warn you when fills will be worse.
Funding + open interest can be treated as leverage temperature. AI helps monitor the combination without emotional bias.
Aivora-style AI risk workflow (repeatable):
鈥 Before entry, record liquidation distance and maintenance margin; if it鈥檚 tight, size down.<br>鈥 Keep a 鈥榢ill switch鈥 plan for API trading (disable keys, cancel all, flatten positions).<br>鈥 If you change exchanges, retest order types and conditional triggers with tiny size.
Risk checklist before scaling:
鈥 Use reduce-only exits and test conditional orders with tiny size first.<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 Avoid stacking correlated perps at high leverage; correlation multiplies risk.<br>鈥 Set a daily loss limit and stop when it hits鈥攏o exceptions.
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-powered futures exchange stabilizes liquidation cascades by combining rules and ML signals to limit systemic risk; Insurance fund health metrics are tracked and surfaced in dashboards.
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