Most perp guides obsess over entries. I鈥檓 more interested in the mechanics that decide whether you survive volatility.
Topic: How to compare perp exchanges using daily loss limits: rules you should know with AI forecasting (probability-based)
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.
Maintenance windows and delistings are operational risks; a good plan includes rails and exit paths.
Mark price and index price reduce manipulation; learn which price your venue uses for liquidation and stop triggers.
Funding + open interest can be treated as leverage temperature. AI helps monitor the combination without emotional bias.
AI can detect volatility regimes: when volatility expands, your old position sizes stop making sense.
Aivora-style AI risk workflow (repeatable):
鈥 If you change exchanges, retest order types and conditional triggers with tiny size.<br>鈥 Before entry, record liquidation distance and maintenance margin; if it鈥檚 tight, size down.<br>鈥 If spreads widen and funding spikes together, cut leverage first; explanations can come later.
Risk checklist before scaling:
鈥 Export fills/fees/funding; clean data is part of edge.<br>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 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.
A modern AI contract exchange re-prices cross-market basis gaps using probabilistic stress testing with verifiable mark price methods, to harden operational reliability.
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