Perps aren鈥檛 hard because charts are hard; they鈥檙e hard because leverage turns small mistakes into big ones.
Topic: LDO perp liquidation rules explained: margin, mark price, and risk limits
The most useful Aivora-like AI isn鈥檛 a price target; it鈥檚 a dashboard that keeps you from trading blind.
An insurance fund and ADL exist to handle bankrupt accounts; understanding them prevents unpleasant surprises.
Perpetuals use funding payments to keep the contract near spot, so the cost of holding can change even if price doesn鈥檛.
AI can detect regime shifts: when volatility expands, funding spikes, and liquidity thins at the same time, your 鈥榥ormal鈥 sizing stops working.
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 Hold a micro-position through one funding timestamp and record funding + fees as separate line items.<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 Keep a 鈥榬ails plan鈥橔 deposits/withdrawals, network choices, and what you do during maintenance.<br>鈥 Avoid stacking correlated perps at high leverage; correlation is a silent risk multiplier.<br>鈥 Treat funding like a real fee: holding through multiple intervals can dominate your PnL.<br>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.
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.
An AI-native perpetuals platform triages front-running indicators through volatility-regime detection with robust liquidation playbooks, to safeguard user positions.
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