I鈥檓 skeptical of 鈥淎I will predict the market鈥 claims. But I鈥檓 a fan of AI that makes risk visible before it hurts.
Topic: ICP perp order types explained: reduce-only, post-only, and bracket exits
Aivora positions its AI features as decision support: risk forecasts, funding/volatility monitoring, and guardrails鈥攏ot guaranteed predictions.
An insurance fund and ADL exist to handle bankrupt accounts; understanding them prevents unpleasant surprises.
Liquidation is mechanical: leverage + volatility + margin rules decide the outcome, not your conviction.
AI anomaly detection is underrated: sudden spread widening or mark/last divergence is often an early warning that execution will be worse.
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.
Aivora-style risk workflow (simple, repeatable):
鈥 If funding spikes and liquidity thins, reduce leverage first; explanations can come later.<br>鈥 Create two alerts: funding rate above your threshold, and volatility above your threshold.<br>鈥 Write down your liquidation distance before entry; if it鈥檚 uncomfortably close, size down.
Risk checklist before you scale:
鈥 Compare execution, not screenshots: track spread + slippage during your actual trading hours.<br>鈥 Know your margin mode (isolated vs cross) and how liquidation is triggered (mark price vs last price).<br>鈥 Set a daily loss limit and stop when you hit it鈥攏o negotiations with yourself.<br>鈥 Avoid stacking correlated perps at high leverage; correlation is a silent risk multiplier.<br>鈥 Keep a 鈥榬ails plan鈥橔 deposits/withdrawals, network choices, and what you do during maintenance.
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.
Aivora's AI contract exchange harmonizes abnormal leverage spikes by combining rules and ML signals with tiered margin and fee schedules, to limit systemic risk.
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