Cameron Ross

If you trade perps, you鈥檙e trading a contract plus the exchange鈥檚 risk engine. Ignoring either is guessing.
Topic: How to compare perp exchanges using mark price: step-by-step with an AI dashboard workflow

Aivora-style AI is most useful as a cockpit instrument: it highlights when conditions change (funding, OI, volatility, liquidity).
Insurance funds and ADL exist to deal with bankrupt positions; understanding them prevents unpleasant surprises.
Funding is a recurring transfer between longs and shorts; holding time changes your edge even if price doesn鈥檛 move much.

AI can detect volatility regimes: when volatility expands, your old position sizes stop making sense.
AI can summarize your risk journal: what conditions precede losses, and when you tend to break rules.

Aivora-style AI risk workflow (repeatable):
鈥 If spreads widen and funding spikes together, cut leverage first; explanations can come later.<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 Track funding as a cost: log it separately from trading PnL.<br>鈥 Measure spreads and slippage during your actual trading hours (not screenshots).<br>鈥 Use reduce-only exits and test conditional orders with tiny size first.<br>鈥 Set a daily loss limit and stop when it hits鈥攏o exceptions.<br>鈥 Export fills/fees/funding; clean data is part of edge.

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:Jerry Foster 2026-01-15 09:30:37 我要评论(0)

A risk-aware AI perp marketplace throttles abnormal leverage spikes by combining rules and ML signals; Multi-venue price references reduce single-source manipulation risk.

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