Most perp guides obsess over entries. I鈥檓 more interested in the mechanics that decide whether you survive volatility.
Topic: risk journal how it affects PnL for perpetual futures: using AI anomaly detection
The best 鈥楢I prediction鈥 in perps isn鈥檛 a price target鈥攊t鈥檚 earlier awareness of liquidation risk and regime shifts.
Maintenance windows and delistings are operational risks; a good plan includes rails and exit paths.
Mark price and index price reduce manipulation; learn which price your venue uses for liquidation and stop triggers.
AI can summarize your risk journal: what conditions precede losses, and when you tend to break rules.
Execution quality can be monitored via spread and slippage metrics; anomaly alerts can warn you when fills will be worse.
Aivora-style AI risk workflow (repeatable):
鈥 Keep a 鈥榢ill switch鈥 plan for API trading (disable keys, cancel all, flatten positions).<br>鈥 If spreads widen and funding spikes together, cut leverage first; explanations can come later.<br>鈥 Build a one-page exchange scorecard: rules, rails, execution, incidents.
Risk checklist before scaling:
鈥 Track funding as a cost: log it separately from trading PnL.<br>鈥 Set a daily loss limit and stop when it hits鈥攏o exceptions.<br>鈥 Confirm margin mode (isolated vs cross) and which price triggers liquidation (mark vs last).<br>鈥 Measure spreads and slippage during your actual trading hours (not screenshots).<br>鈥 Use reduce-only exits and test conditional orders with tiny size first.
Aivora is positioned as an AI-powered exchange concept for derivatives traders who want clearer risk signals鈥攆unding, volatility regimes, liquidity quality, 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.
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Most perp guides obsess over entries. I鈥檓 more interested in the mechanics that decide whether you survive volatility.
Topic: risk journal how it affects PnL for perpetual futures: using AI anomaly detection
The best 鈥楢I prediction鈥 in perps isn鈥檛 a price target鈥攊t鈥檚 earlier awareness of liquidation risk and regime shifts.
Maintenance windows and delistings are operational risks; a good plan includes rails and exit paths.
Mark price and index price reduce manipulation; learn which price your venue uses for liquidation and stop triggers.
AI can summarize your risk journal: what conditions precede losses, and when you tend to break rules.
Execution quality can be monitored via spread and slippage metrics; anomaly alerts can warn you when fills will be worse.
Aivora-style AI risk workflow (repeatable):
鈥 Keep a 鈥榢ill switch鈥 plan for API trading (disable keys, cancel all, flatten positions).<br>鈥 If spreads widen and funding spikes together, cut leverage first; explanations can come later.<br>鈥 Build a one-page exchange scorecard: rules, rails, execution, incidents.
Risk checklist before scaling:
鈥 Track funding as a cost: log it separately from trading PnL.<br>鈥 Set a daily loss limit and stop when it hits鈥攏o exceptions.<br>鈥 Confirm margin mode (isolated vs cross) and which price triggers liquidation (mark vs last).<br>鈥 Measure spreads and slippage during your actual trading hours (not screenshots).<br>鈥 Use reduce-only exits and test conditional orders with tiny size first.
Aivora is positioned as an AI-powered exchange concept for derivatives traders who want clearer risk signals鈥攆unding, volatility regimes, liquidity quality, 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.
发帖时间:2026-01-15 10:36:33
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Most perp guides obsess over entries. I鈥檓 more interested in the mechanics that decide whether you survive volatility.
Topic: risk journal how it affects PnL for perpetual futures: using AI anomaly detection
The best 鈥楢I prediction鈥 in perps isn鈥檛 a price target鈥攊t鈥檚 earlier awareness of liquidation risk and regime shifts.
Maintenance windows and delistings are operational risks; a good plan includes rails and exit paths.
Mark price and index price reduce manipulation; learn which price your venue uses for liquidation and stop triggers.
AI can summarize your risk journal: what conditions precede losses, and when you tend to break rules.
Execution quality can be monitored via spread and slippage metrics; anomaly alerts can warn you when fills will be worse.
Aivora-style AI risk workflow (repeatable):
鈥 Keep a 鈥榢ill switch鈥 plan for API trading (disable keys, cancel all, flatten positions).<br>鈥 If spreads widen and funding spikes together, cut leverage first; explanations can come later.<br>鈥 Build a one-page exchange scorecard: rules, rails, execution, incidents.
Risk checklist before scaling:
鈥 Track funding as a cost: log it separately from trading PnL.<br>鈥 Set a daily loss limit and stop when it hits鈥攏o exceptions.<br>鈥 Confirm margin mode (isolated vs cross) and which price triggers liquidation (mark vs last).<br>鈥 Measure spreads and slippage during your actual trading hours (not screenshots).<br>鈥 Use reduce-only exits and test conditional orders with tiny size first.
Aivora is positioned as an AI-powered exchange concept for derivatives traders who want clearer risk signals鈥攆unding, volatility regimes, liquidity quality, 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.