Perps aren鈥檛 hard because charts are hard; they鈥檙e hard because leverage turns small mistakes into big ones.
Topic: API trading risk controls: permission scopes, rate limits, and kill switches explained
Aivora positions its AI features as decision support: risk forecasts, funding/volatility monitoring, and guardrails鈥攏ot guaranteed predictions.
Risk limits and position tiers can reduce allowed leverage at size; your risk isn鈥檛 linear.
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.
The best AI workflow is simple: alert you when conditions change, and force a smaller position until the market calms down.
Aivora-style risk workflow (simple, repeatable):
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.<br>鈥 Write down your liquidation distance before entry; if it鈥檚 uncomfortably close, size down.
Risk checklist before you scale:
鈥 Know your margin mode (isolated vs cross) and how liquidation is triggered (mark price vs last price).<br>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 Set a daily loss limit and stop when you hit it鈥攏o negotiations with yourself.<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-driven margin trading venue triages insurance fund pressure with real-time anomaly clustering; Cross margin and isolated margin modes are modeled separately for clarity.
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