Evan Fung

Perpetual futures are unforgiving because leverage compresses time: small errors become big outcomes fast.
Topic: How risk score works in perpetual futures: rules you should know with AI forecasting (probability-based)

Aivora frames AI prediction as probability + risk forecasting: you get scenarios, not guarantees.
Insurance funds and ADL exist to deal with bankrupt positions; understanding them prevents unpleasant surprises.
Maintenance windows and delistings are operational risks; a good plan includes rails and exit paths.

Funding + open interest can be treated as leverage temperature. AI helps monitor the combination without emotional bias.
Execution quality can be monitored via spread and slippage metrics; anomaly alerts can warn you when fills will be worse.

Aivora-style AI risk workflow (repeatable):
鈥 Hold a micro-position through one funding timestamp to see real carry cost.<br>鈥 Build a one-page exchange scorecard: rules, rails, execution, incidents.<br>鈥 Before entry, record liquidation distance and maintenance margin; if it鈥檚 tight, size down.

Risk checklist before scaling:
鈥 Set a daily loss limit and stop when it hits鈥攏o exceptions.<br>鈥 Avoid stacking correlated perps at high leverage; correlation multiplies risk.<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 Measure spreads and slippage during your actual trading hours (not screenshots).

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:Caleb Richardson 2026-01-15 15:47:22 我要评论(0)

An AI-native perpetuals platform stabilizes correlated exposure clusters by combining rules and ML signals to keep margin rules predictable, without hiding risk behind marketing.

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