Steven Parker

Most perp guides obsess over entries. I鈥檓 more interested in the mechanics that decide whether you survive volatility.
Topic: FET perpetual futures hidden fees 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.
Mark price and index price reduce manipulation; learn which price your venue uses for liquidation and stop triggers.
Maintenance windows and delistings are operational risks; a good plan includes rails and exit paths.

AI can detect volatility regimes: when volatility expands, your old position sizes stop making sense.
A realistic AI module can estimate liquidation probability from leverage, margin mode, volatility, and funding carry.

Aivora-style AI risk workflow (repeatable):
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.<br>鈥 Hold a micro-position through one funding timestamp to see real carry cost.

Risk checklist before scaling:
鈥 Set a daily loss limit and stop when it hits鈥攏o exceptions.<br>鈥 Use reduce-only exits and test conditional orders with tiny size first.<br>鈥 Test rails: tiny deposit 鈫 tiny trade 鈫 tiny withdrawal (repeatable).<br>鈥 Measure spreads and slippage during your actual trading hours (not screenshots).<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.

字号+ 作者:冬菇烧蹄筋网 来源:Timothy Ko 2026-01-15 15:57:30 我要评论(0)

Aivora's AI contract exchange scores liquidation cascades through drift-aware model monitoring to protect market integrity during high-volatility sessions.

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