Build an Auditable Discounted Cash Flow Scenario Application

A corporate finance analyst reviewing a valuation model.

Turn a documented operating forecast into an enterprise-value range. Expose cash-flow timing, reinvestment, discount-rate assumptions, and terminal-value dependence.

Key: scenario_id + forecast_year + cash_flow_line.

Fields: operating_profit, cash_tax, depreciation, capital_spend, working_capital_change, discount_rate.

Distinguish firm cash flow from equity cash flow. Specify year-end or midyear discounting.

Reconcile forecast assumptions to a cash-flow bridge.

Discount firm cash flows under the stated timing convention.

Calculate terminal value with feasibility checks.

Export scenario sensitivities and an assumption approval record.

A forecast grid, cash-flow waterfall, sensitivity matrix, and terminal-value share warning.

A formula-transparent valuation workbook.

A scenario report with the dominant assumptions and unresolved evidence.

Runnable local application, setup commands, and a dependency lockfile.

Versioned input data, data dictionary, acquisition instructions, and rights notes.

Calculation traces, source references, assumption records, and exported review artifacts.

A deterministic baseline and tests for normal, incomplete, contradictory, and failure-recovery cases.

A recorded complete workflow with a reproducible manifest and explicit limitations.

Reject perpetual-growth cases where discount rate is not greater than growth.

Do not discount equity cash flows with a firm discount rate.

Increasing the discount rate lowers positive fixed cash-flow present value.

Terminal cash flow and reinvestment assumptions reconcile.

Use identical cash flows with different discount rates. Value changes without any change in the operating forecast.

The attached starter files are prototype inputs. Expected starter answers are visible. They are not independent holdouts.

Full target: Use public historical statements and a fictional five-year forecast. Supply tax, reinvestment, terminal-growth, and discount-rate assumptions explicitly.

Complete target contracts and expert review remain pending. Public observations are not historical release vintages.

NumPy, SciPy, openpyxl

Use an available model appropriate to the task. Record provider, model identifier, version or retrieval date, settings, cost, and latency. Use deterministic code for calculations. Models may extract, retrieve, or explain evidence. They must not invent missing records, override approval rules, or claim professional authority.

An illustrative value range is not an investment recommendation or certified appraisal.

No fabricated records, source citations, professional endorsements, or expert-adjudication claims.

No future-data leakage into dated decisions, model fitting, or historical valuation inputs.

No unauthorized payments, account restrictions, regulatory filings, or production changes.

No automated appraisal certification, tax-compliance determination, or unsupported fraud accusation.

No concealed uncertainty or silently invented inputs required for a numerical conclusion.

Correct domain calculations and justified methods with documented assumptions. Weight: 30.

Source lineage, temporal integrity, rights checks, and explicit synthetic-data labels. Weight: 25.

A working application with review, export, error handling, and reproducible state. Weight: 20.

Adversarial cases, uncertainty, missing-data behavior, and sensitivity analysis. Weight: 15.

Evidence-linked conclusions that distinguish facts, assumptions, and unresolved judgments. Weight: 10. Score each dimension from zero to two. Weighted score = sum(weight * score / 2). A failed safety gate blocks acceptance.