GAUGE: Grading Agent-Built Financial Models Without a Golden Answer
Quick summary
arXiv:2607.24889v1 Announce Type: cross Abstract: Financial models combine public disclosures with analyst assumptions to produce forecasts and valuations. While some components can be checked mechanically, forecasts, discount rates, and target prices often admit multiple reasonable answers. Existing benchmarks nevertheless tend to grade such outputs against a single expert reference. Using independently built analyst models for the same companies, we find that across 108 directed pairs covering 65 companies, the median single-reference score is 0.33, 92.6% score below 0.70, and no same-vintag
Key takeaways
- arXiv:2607.24889v1 Announce Type: cross Abstract: Financial models combine public disclosures with analyst assumptions to produce forecasts and valuations.
- While some components can be checked mechanically, forecasts, discount rates, and target prices often admit multiple reasonable answers.
- Existing benchmarks nevertheless tend to grade such outputs against a single expert reference.
Why it matters
The importance of “GAUGE: Grading Agent-Built Financial Models Without a Golden Answer” will be measured by what changes in practice. User behavior, access conditions, verifiable performance and responsible-use outcomes are the signals worth following.