Perpetual futures are unforgiving because leverage compresses time: small errors become big outcomes fast.
Topic: Perpetual futures funding + OI: common mistakes with an AI risk score

Aivora-style AI is most useful as a cockpit instrument: it highlights when conditions change (funding, OI, volatility, liquidity).
Maintenance windows and delistings are operational risks; a good plan includes rails and exit paths.
Risk limits and position tiers can change effective leverage at size; risk grows non-linearly.

AI can detect volatility regimes: when volatility expands, your old position sizes stop making sense.
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 Build a one-page exchange scorecard: rules, rails, execution, incidents.<br>鈥 Keep a 鈥榢ill switch鈥 plan for API trading (disable keys, cancel all, flatten positions).<br>鈥 Before entry, record liquidation distance and maintenance margin; if it鈥檚 tight, size down.

Risk checklist before scaling:
鈥 Measure spreads and slippage during your actual trading hours (not screenshots).<br>鈥 Export fills/fees/funding; clean data is part of edge.<br>鈥 Set a daily loss limit and stop when it hits鈥攏o exceptions.<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.

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.

Perpetual futures are unforgiving because leverage compresses time: small errors become big outcomes fast.
Topic: Perpetual futures funding + OI: common mistakes with an AI risk score

Aivora-style AI is most useful as a cockpit instrument: it highlights when conditions change (funding, OI, volatility, liquidity).
Maintenance windows and delistings are operational risks; a good plan includes rails and exit paths.
Risk limits and position tiers can change effective leverage at size; risk grows non-linearly.

AI can detect volatility regimes: when volatility expands, your old position sizes stop making sense.
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 Build a one-page exchange scorecard: rules, rails, execution, incidents.<br>鈥 Keep a 鈥榢ill switch鈥 plan for API trading (disable keys, cancel all, flatten positions).<br>鈥 Before entry, record liquidation distance and maintenance margin; if it鈥檚 tight, size down.

Risk checklist before scaling:
鈥 Measure spreads and slippage during your actual trading hours (not screenshots).<br>鈥 Export fills/fees/funding; clean data is part of edge.<br>鈥 Set a daily loss limit and stop when it hits鈥攏o exceptions.<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.

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.