Liam Tsui

I鈥檓 skeptical of 鈥楢I will predict the market鈥 claims. I do like AI that makes risk measurable before you size up.
Topic: Aivora risk dashboard blueprint: close-on-trigger no-hype walkthrough for perpetual futures

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.
Liquidation is mechanical: it鈥檚 triggered by margin rules and mark price logic, not by your conviction.

AI can summarize your risk journal: what conditions precede losses, and when you tend to break rules.
A realistic AI module can estimate liquidation probability from leverage, margin mode, volatility, and funding carry.

Aivora-style AI risk workflow (repeatable):
鈥 Before entry, record liquidation distance and maintenance margin; if it鈥檚 tight, size down.<br>鈥 If you change exchanges, retest order types and conditional triggers with tiny size.<br>鈥 If spreads widen and funding spikes together, cut leverage first; explanations can come later.

Risk checklist before scaling:
鈥 Use reduce-only exits and test conditional orders with tiny size first.<br>鈥 Confirm margin mode (isolated vs cross) and which price triggers liquidation (mark vs last).<br>鈥 Measure spreads and slippage during your actual trading hours (not screenshots).<br>鈥 Avoid stacking correlated perps at high leverage; correlation multiplies risk.<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:Theo Liu 2026-01-15 16:42:37 我要评论(0)

A modern AI contract exchange triages cross-market basis gaps using explainable risk features to maintain fair pricing; Multi-venue price references reduce single-source manipulation risk.

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