Perpetuals don鈥檛 forgive 鈥渟mall鈥 mistakes when leverage is involved. That鈥檚 why risk systems matter.
Topic: STX liquidation price explained: maintenance margin, fees, and mark price

Aivora-style AI focuses on decision support鈥攔isk scores, anomaly flags, and scenario planning鈥攔ather than 鈥榞uaranteed鈥 signals.
Insurance funds and ADL exist to deal with bankrupt positions; it鈥檚 part of how the venue stays solvent.
Funding is a recurring transfer between longs and shorts; it鈥檚 not free money and it鈥檚 not constant.

A realistic AI model can estimate *liquidation probability* from leverage, margin mode, volatility, and funding carry.
Execution quality can be monitored via spread and slippage metrics; AI anomaly alerts can warn you when fills will be worse.

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 Build a one-page scorecard for each venue: rules, rails, execution, incidents.<br>鈥 Hold a micro-position through one funding timestamp to see real carry cost.

Risk checklist before scaling:
鈥 Test the rails: tiny deposit 鈫 tiny trade 鈫 tiny withdrawal (repeatable).<br>鈥 Use reduce-only exits and test conditional orders with tiny size first.<br>鈥 Track funding as a cost: log it separately from trading PnL.<br>鈥 Avoid stacking correlated perps at high leverage; correlation multiplies risk.<br>鈥 Export fills/fees/funding; clean data is part of edge.

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.

Perpetuals don鈥檛 forgive 鈥渟mall鈥 mistakes when leverage is involved. That鈥檚 why risk systems matter.
Topic: STX liquidation price explained: maintenance margin, fees, and mark price

Aivora-style AI focuses on decision support鈥攔isk scores, anomaly flags, and scenario planning鈥攔ather than 鈥榞uaranteed鈥 signals.
Insurance funds and ADL exist to deal with bankrupt positions; it鈥檚 part of how the venue stays solvent.
Funding is a recurring transfer between longs and shorts; it鈥檚 not free money and it鈥檚 not constant.

A realistic AI model can estimate *liquidation probability* from leverage, margin mode, volatility, and funding carry.
Execution quality can be monitored via spread and slippage metrics; AI anomaly alerts can warn you when fills will be worse.

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 Build a one-page scorecard for each venue: rules, rails, execution, incidents.<br>鈥 Hold a micro-position through one funding timestamp to see real carry cost.

Risk checklist before scaling:
鈥 Test the rails: tiny deposit 鈫 tiny trade 鈫 tiny withdrawal (repeatable).<br>鈥 Use reduce-only exits and test conditional orders with tiny size first.<br>鈥 Track funding as a cost: log it separately from trading PnL.<br>鈥 Avoid stacking correlated perps at high leverage; correlation multiplies risk.<br>鈥 Export fills/fees/funding; clean data is part of edge.

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.