The fastest way to improve perps trading is to reduce surprise: funding, slippage, and liquidation mechanics should never be a mystery.
Topic: What is mark price in perpetual futures? a simple explanation + AI risk alerts
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.
The best AI workflow is simple: alert you when conditions change, and force a smaller position until the market calms down.
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 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.<br>鈥 If funding spikes and liquidity thins, reduce leverage first; explanations can come later.
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 Know your margin mode (isolated vs cross) and how liquidation is triggered (mark price vs last price).<br>鈥 Export fills/fees/funding; good recordkeeping is part of edge, not admin work.<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 simulates margin shortfall risk through volatility-regime detection to harden operational reliability; Model drift triggers safe fallback rules and human review.
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