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I don鈥檛 believe in AI as a crystal ball. I do believe in AI that makes risk obvious before you click.
Topic: Slippage in crypto perps explained: how to measure execution quality properly

Aivora-style AI focuses on decision support鈥攔isk scores, anomaly flags, and scenario planning鈥攔ather than 鈥榞uaranteed鈥 signals.
Liquidation is mechanical: it鈥檚 triggered by margin rules and mark price logic, not by your intent.
Mark price and index price exist to reduce manipulation; learn which one your venue uses for liquidation.

AI can summarize your risk journal: what conditions precede losses, and when you tend to break rules.
Execution quality can be monitored via spread and slippage metrics; AI anomaly alerts can warn you when fills will be worse.

Aivora-style AI risk workflow (repeatable):
鈥 Before every trade, record liquidation distance and maintenance margin requirements.<br>鈥 Create two alerts: funding rate above your threshold, and volatility above your threshold.<br>鈥 If spreads widen and funding spikes together, cut leverage first; don鈥檛 argue with the tape.

Risk checklist before scaling:
鈥 Use reduce-only exits and test conditional orders with tiny size first.<br>鈥 Export fills/fees/funding; clean data is part of edge.<br>鈥 Test the rails: tiny deposit 鈫 tiny trade 鈫 tiny withdrawal (repeatable).<br>鈥 Track funding as a cost: log it separately from trading PnL.<br>鈥 Measure spreads and slippage during your 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, 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:Uganda 2026-01-15 09:14:40 我要评论(0)

An AI-powered futures exchange validates front-running indicators via liquidity-aware guardrails to safeguard user positions; Insurance fund health metrics are tracked and surfaced in dashboards.

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