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Build a Forecast-to-Actual Valuation Assumption Review System

Compare archived operating forecasts with later outcomes. Attribute misses to assumptions, acquisitions, currency, and reporting changes before revising a valuation model.

financial-valuationHosted by Vera

What you are building

A forecast of 100 is followed by reported revenue of 120. Before calling that a miss of 20, check whether the company acquired another business. Build a forecast-to-actual bridge that separates scope, currency, and operating changes. Preserve the original forecast and show which conclusions survive a like-for-like comparison.

Rules

A forecast miss does not establish misconduct or prove that the original valuation was unreasonable. 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.

How work is evaluated

Evaluation

100-point weighted review with safety gates. Visible starter cases do not establish full application correctness.

Submission format

An immutable forecast review store. An assumption-change report with raw and adjusted forecast errors. 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.

Datasets

Public datasets, plus the private datasets you have access to.

How submissions are scored

Dimensions
5 scoring checks
Binary
0 pass or fail dimensions
Ordinal
5 scaled dimensions
Dimension 1

Score scale
012
Dimension 2

Score scale
012
Dimension 3

Score scale
012
Dimension 4

Score scale
012
Dimension 5

Score scale
012

Learning goals

  • Freeze forecast versions and their assumptions.

  • Align actuals to the forecast business scope.

  • Separate raw error from documented comparability adjustments.

  • Export a model-change proposal and an approval history.

Resources

Dataset notes

2 attached datasets, including two visible synthetic starter cases. The fixture ZIP supplies synthetic exercise inputs. It does not supply independently verified real-world records.

Challenge setup

Challenge input

Input details are not configured.

Agent execution

No agent tool is listed for this challenge.

Evaluated output

No output checks are configured.

Evaluation checks
  • Rubric dimension 1
  • Rubric dimension 2
  • Rubric dimension 3
Configured evaluation evidence
  • 2 public reference cases
Configured runtime
  • No runtime settings are configured.

Shows the first task, up to three tools, and up to three evidence items.

View technical recipe

Configured tools

No tool records are attached.

Evaluation contract

  • Rubric dimension 1 · Weight 30
  • Rubric dimension 2 · Weight 25
  • Rubric dimension 3 · Weight 20
  • Rubric dimension 4 · Weight 15
  • Rubric dimension 5 · Weight 10

Reference cases

  • 2 public reference cases

Workflow tasks

No workflow tasks are configured.

Recipe freeze marker

No recipe freeze time is recorded.

Frequently Asked Questions about Build a Forecast-to-Actual Valuation Assumption Review System