Quanta infiniX Algorithm Metrics

Metrics are the verification layer for infiniX. They show whether the strategy is achieving intended operating outcomes under live conditions.

Outcome Verification Framework

Use metrics to answer four practical questions:

1. Is capital being reused efficiently?
2. Is execution quality stable after costs?
3. Is risk staying inside limits?
4. Is runtime behaviour healthy and observable?

1) Capital Efficiency and Turnover

Key signals:

• TVIC: live portfolio valuation context.
• Trade vs. HODL: active execution value-add context.
• Cmax and Cap Ratio: capital deployment pressure.

Use these to judge whether turnover is productive rather than simply frequent.

2) Execution Quality and Performance

Key signals:

• uPNL: live unrealised performance state.
• Daily EBIT / % Daily EBIT / Annual EBIT: operating profitability snapshots.
• Sortino (proxy): downside-aware quality lens.

Evaluate these alongside fee conditions and regime context.

3) Risk and Exposure Control

Key signals:

• Hist Low / Hist High / Price Range: regime breadth context.
• sigma and model-state values: posting suitability context.
• delta metrics: quote displacement and adjustment behaviour.

These help confirm that risk gates and inventory controls are functioning as intended.

4) Runtime Health and Observability

Key signals:

• Refresh Speed: full-cycle latency profile.
• Code Proc Time: strategy compute overhead.
• Last API Call: data freshness and interaction continuity.

Operational degradation should be treated as a control issue, not only a performance issue.

Practical Review Sequence

1. Check runtime health metrics first.
2. Check regime and gating context second.
3. Check performance quality metrics third.
4. Check capital and exposure metrics fourth.

This order reduces false conclusions during noisy market periods.

Metrics support decisions; they do not guarantee outcomes.