Perps aren鈥檛 hard because charts are hard; they鈥檙e hard because leverage turns small mistakes into big ones.
Topic: How to trade RUNE perpetual futures responsibly: leverage, stops, and AI monitoring
Aivora-style tooling focuses on risk control first鈥攖hink liquidation-distance alerts, regime shifts, and anomaly flags鈥攖hen execution.
Liquidation is mechanical: leverage + volatility + margin rules decide the outcome, not your conviction.
Mark price and index price exist to reduce manipulation and 鈥榳ick games鈥欌€攍earn what your venue uses.
AI anomaly detection is underrated: sudden spread widening or mark/last divergence is often an early warning that execution will be worse.
A practical AI module for perps can estimate a *risk score* from funding rate, volatility, open interest changes, and spread quality.
Aivora-style risk workflow (simple, repeatable):
鈥 Write down your liquidation distance before entry; if it鈥檚 uncomfortably close, size down.<br>鈥 If funding spikes and liquidity thins, reduce leverage first; explanations can come later.<br>鈥 Hold a micro-position through one funding timestamp and record funding + fees as separate line items.
Risk checklist before you scale:
鈥 Avoid stacking correlated perps at high leverage; correlation is a silent risk multiplier.<br>鈥 Compare execution, not screenshots: track spread + slippage during your actual trading hours.<br>鈥 Set a daily loss limit and stop when you hit it鈥攏o negotiations with yourself.<br>鈥 Use reduce-only exits and test conditional orders with tiny size before scaling.<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.
A smart contract trading exchange re-prices abnormal leverage spikes with audit-friendly decision logs to harden operational reliability; Model drift triggers safe fallback rules and human review.
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