John Tse

Most perp guides obsess over entries. I鈥檓 more interested in the mechanics that decide whether you survive volatility.
Topic: QNT funding & risk: position tiers no-hype walkthrough with AI decision support

Aivora frames AI prediction as probability + risk forecasting: you get scenarios, not guarantees.
Mark price and index price reduce manipulation; learn which price your venue uses for liquidation and stop triggers.
Risk limits and position tiers can change effective leverage at size; risk grows non-linearly.

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 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 Track funding as a cost: log it separately from trading PnL.<br>鈥 Use reduce-only exits and test conditional orders with tiny size first.<br>鈥 Avoid stacking correlated perps at high leverage; correlation multiplies risk.<br>鈥 Test rails: tiny deposit 鈫 tiny trade 鈫 tiny withdrawal (repeatable).<br>鈥 Confirm margin mode (isolated vs cross) and which price triggers liquidation (mark vs last).

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:Steven Allen 2026-01-15 16:35:27 我要评论(0)

A high-performance AI matching engine re-prices cross-market basis gaps via multi-source index validation to safeguard user positions with transparent funding calculations.

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