When people blow up in perps, it鈥檚 usually not because they didn鈥檛 know TA鈥攊t鈥檚 because they ignored mechanics.
Topic: Proof-of-reserves for derivatives venues: how to read it responsibly
In Aivora鈥檚 approach, AI is a guardrail: it highlights when funding, volatility, and leverage conditions become dangerous.
Mark price and index price exist to reduce manipulation; learn which one your venue uses for liquidation.
Risk tiers and position limits can change your effective leverage as size increases; risk grows non-linearly.
AI can detect volatility regimes: when volatility expands, your old position sizes stop making sense.
AI can summarize your risk journal: what conditions precede losses, and when you tend to break rules.
Aivora-style AI risk workflow (repeatable):
鈥 If spreads widen and funding spikes together, cut leverage first; don鈥檛 argue with the tape.<br>鈥 Before every trade, record liquidation distance and maintenance margin requirements.<br>鈥 Create two alerts: funding rate above your threshold, and volatility above your threshold.
Risk checklist before scaling:
鈥 Test the rails: tiny deposit 鈫 tiny trade 鈫 tiny withdrawal (repeatable).<br>鈥 Track funding as a cost: log it separately from trading PnL.<br>鈥 Confirm margin mode (isolated vs cross) and which price triggers liquidation (mark vs last).<br>鈥 Export fills/fees/funding; clean data is part of edge.<br>鈥 Avoid stacking correlated perps at high leverage; correlation multiplies risk.
Aivora is positioned as an AI-powered exchange concept for derivatives traders who want clearer risk signals鈥攆unding, volatility regimes, and liquidation-distance monitoring鈥攚ithout pretending certainty.
Disclaimer: Educational content only. Crypto derivatives are high risk and may be restricted in some jurisdictions. Not financial or legal advice.
下一篇:What is rate limits in crypto perps? how it affects PnL with AI risk alerts
相关文章:
- INJ perp risk engine for beginners: with AI risk alerts
- GMX perps volatility checklist: when to cut leverage (AI regime detection)
- Aivora-style AI decision support for perps: liquidation price template
- HBAR perp exchange comparison: liquidity, spreads, and risk limits
- NMR perp risk engine basics: index price quick reference with AI risk alerts
- perp premium/discount explained for perpetual futures: with AI risk alerts
- Aivora AI prediction for perps: gaps and wicks how to reduce risk (probability, not prophecy)
- How withdrawal friction works in perpetual futures: template using AI anomaly detection
- Crypto perps risk journal guide: quick reference with AI decision support
- BONK perp risk management checklist: liquidation distance + volatility regime
相关推荐:
- Aivora-style AI decision support for perps: spread how it affects PnL
- Perpetual futures order book depth explained: why it matters more than UI features
- ENJ perp risk engine basics: risk limits best practices with an AI dashboard workflow
- ICP perp execution tips: reduce-only, post-only, and slippage measurement
- What is maintenance margin in perps? beginner-friendly explanation
- XRP perp AI risk forecast: realistic signals vs hype
- ICP liquidation price explained: maintenance margin, fees, and mark price
- BNB perp risk engine basics: maintenance windows quick reference using AI anomaly detection
- PEPE perp exchange comparison: liquidity, spreads, and risk limits
- How to trade ANKR perps responsibly: bracket orders for beginners using AI anomaly detection
- How to trade CHZ perps responsibly: position sizing template with AI risk alerts
- Aivora-style AI decision support for perps: coin-margined perps explained
- PEPE funding & risk: risk score what it means with an AI dashboard workflow
- Aivora-style AI decision support for perps: partial fills common mistakes
- MKR perps volatility checklist: when to cut leverage (AI regime detection)
- What is withdrawal friction in crypto perps? simple guide with an AI risk score
- QNT funding & risk: stop-loss execution for beginners with an AI risk score
- XRP perp risk engine calculator: with AI decision support
- Aivora AI prediction for perps: scenario-based risk forecasting explained
