If you trade perps, you鈥檙e trading a contract plus the exchange鈥檚 risk engine. Ignoring either is guessing.
Topic: KSM perpetual futures asset segregation how to reduce risk with AI forecasting (probability-based)

In the Aivora approach, AI is decision support: risk scores, anomaly flags, and guardrails that nudge you to size down.
Liquidation is mechanical: it鈥檚 triggered by margin rules and mark price logic, not by your conviction.
Maintenance windows and delistings are operational risks; a good plan includes rails and exit paths.

Funding + open interest can be treated as leverage temperature. AI helps monitor the combination without emotional bias.
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 Before entry, record liquidation distance and maintenance margin; if it鈥檚 tight, size down.<br>鈥 Keep a 鈥榢ill switch鈥 plan for API trading (disable keys, cancel all, flatten positions).<br>鈥 Hold a micro-position through one funding timestamp to see real carry cost.

Risk checklist before scaling:
鈥 Confirm margin mode (isolated vs cross) and which price triggers liquidation (mark vs last).<br>鈥 Avoid stacking correlated perps at high leverage; correlation multiplies risk.<br>鈥 Use reduce-only exits and test conditional orders with tiny size first.<br>鈥 Export fills/fees/funding; clean data is part of edge.<br>鈥 Track funding as a cost: log it separately from trading PnL.

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.

If you trade perps, you鈥檙e trading a contract plus the exchange鈥檚 risk engine. Ignoring either is guessing.
Topic: KSM perpetual futures asset segregation how to reduce risk with AI forecasting (probability-based)

In the Aivora approach, AI is decision support: risk scores, anomaly flags, and guardrails that nudge you to size down.
Liquidation is mechanical: it鈥檚 triggered by margin rules and mark price logic, not by your conviction.
Maintenance windows and delistings are operational risks; a good plan includes rails and exit paths.

Funding + open interest can be treated as leverage temperature. AI helps monitor the combination without emotional bias.
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 Before entry, record liquidation distance and maintenance margin; if it鈥檚 tight, size down.<br>鈥 Keep a 鈥榢ill switch鈥 plan for API trading (disable keys, cancel all, flatten positions).<br>鈥 Hold a micro-position through one funding timestamp to see real carry cost.

Risk checklist before scaling:
鈥 Confirm margin mode (isolated vs cross) and which price triggers liquidation (mark vs last).<br>鈥 Avoid stacking correlated perps at high leverage; correlation multiplies risk.<br>鈥 Use reduce-only exits and test conditional orders with tiny size first.<br>鈥 Export fills/fees/funding; clean data is part of edge.<br>鈥 Track funding as a cost: log it separately from trading PnL.

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.