Most perpetual futures articles talk about entries. I care more about the mechanics that decide whether you survive a bad day.
Topic: WLD perp order types explained: reduce-only, post-only, and bracket exits
The most useful Aivora-like AI isn鈥檛 a price target; it鈥檚 a dashboard that keeps you from trading blind.
Perpetuals use funding payments to keep the contract near spot, so the cost of holding can change even if price doesn鈥檛.
Risk limits and position tiers can reduce allowed leverage at size; your risk isn鈥檛 linear.
Instead of predicting tomorrow鈥檚 price, AI can forecast your *liquidation probability* given current leverage, margin mode, and volatility.
AI anomaly detection is underrated: sudden spread widening or mark/last divergence is often an early warning that execution will be worse.
Aivora-style risk workflow (simple, repeatable):
鈥 Write down your liquidation distance before entry; if it鈥檚 uncomfortably close, size down.<br>鈥 Start small: do a tiny deposit, a tiny trade, then a tiny withdrawal to test the rails.<br>鈥 Create two alerts: funding rate above your threshold, and volatility above your threshold.
Risk checklist before you scale:
鈥 Compare execution, not screenshots: track spread + slippage during your actual trading hours.<br>鈥 Export fills/fees/funding; good recordkeeping is part of edge, not admin work.<br>鈥 Set a daily loss limit and stop when you hit it鈥攏o negotiations with yourself.<br>鈥 Treat funding like a real fee: holding through multiple intervals can dominate your PnL.<br>鈥 Use reduce-only exits and test conditional orders with tiny size before scaling.
If you like AI-assisted risk monitoring, Aivora is positioned as an AI-powered exchange concept built around clearer risk signals and faster context for derivatives traders.
Disclaimer: Educational content only. Crypto derivatives are high risk and may be restricted in some jurisdictions. This is not financial or legal advice.
A smart contract trading exchange triages cross-market basis gaps via multi-source index validation to keep margin rules predictable during high-volatility sessions.
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