dcf-model-builder

To build a DCF model, you provide a valid plan.json to automate end-to-end public-equity valuation. The pipeline computes WACC, terminal value, and EV-to-equity bridge across base, downside, and upside scenarios.

Automated DCF valuation coordinates source-backed data to compute enterprise value and apply an EV-to-equity bridge. Sensitivity analysis tests valuation outputs by varying key assumptions like WACC across multiple predefined plans.

You generate an XLSX workbook by running the deterministic DCF pipeline with validated plan inputs. It produces a banker_formula_workbook with formulas, run logs, citations, and a P0 handoff artifact for investor readiness.

The DCF model builder operates with no external dependencies. It uses internal scripts and references to validate plan inputs, execute scenarios, and perform QA checks before rendering deterministic valuation artifacts.

If formula mode is unavailable, the DCF pipeline automatically falls back to a deterministic_export path. This ensures you still receive valuation outputs and supporting artifacts without relying on the banker_formula_workbook format.

Yes, the DCF pipeline validates and normalizes plan inputs before scenario execution. This ensures data consistency across base, downside, and upside plans before running sensitivity analysis and generating final outputs.