Methodology v0.1 · Draft
How Vision Grade works.
This public draft explains the scoring structure used by the current AlgoNexa product sample. It is intended for transparency and review before production ratings are offered.
Vision Grade assesses evidence quality and strategy characteristics. It does not predict future returns, guarantee profitability, or constitute investment advice.
Score dimensions
Robustness
30%Stress behavior and parameter sensitivity
Risk discipline
25%Drawdown, concentration, and exposure
Stability
20%Consistency across windows and regimes
Execution quality
15%Costs, slippage, and implementation evidence
Model confidence
10%Evidence completeness and unresolved uncertainty
Required inputs
- • Locked strategy version
- • Evidence manifest and data window
- • Cost and execution assumptions
- • Validation results and known gaps
Regrade triggers
- • Source or parameter change
- • New validation or forward evidence
- • Evidence integrity issue
- • Published methodology change
Integrity rules
- 1. The same normalized inputs, evidence package, and methodology version must produce the same result.
- 2. A published assessment cannot silently change; new inputs create a new snapshot.
- 3. Missing evidence reduces confidence and must remain visible to the reader.
- 4. Commercial relationships cannot change the computed score.
See the methodology in context
Trace a sample grade back to its evidence.