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Financial Statement Forecasting in Equity Valuation

Behind almost every equity valuation sits a financial statement forecast model that turns assumptions about a business into projected income statements, balance sheets and cash flows. This module explains why and how such models are built, how to choose the drivers and structure that fit a particular company, and how to convert the model's output into an estimate of value per share.

What you will learn

1. Explain why analysts build financial statement forecast models and how a linked forecast of the income statement, balance sheet and cash flows is constructed.

  • Forecast models supply cash flows for valuation, enforce consistency and enable scenario analysis.
  • Revenue: top-down (market size x share, GDP-linked), bottom-up (volume x price) or hybrid.
  • Separate fixed and variable costs to capture operating leverage.
  • Working capital via days ratios; fixed assets roll forward with capex and depreciation.
  • Cash or a revolver is the balancing item that links the three statements.

2. Evaluate whether the structure, drivers and horizon of an equity valuation model suit the characteristics of the company being valued.

  • Choose revenue drivers that mirror the business model (subscribers, stores, capacity, volumes, loans).
  • Match cost and capital detail to the industry; capture operating leverage where fixed costs are high.
  • Extend the explicit horizon until growth and margins reach a steady state.
  • Check consistency: growth needs reinvestment; margins and ROIC must be plausible.
  • Use scenarios on the most important drivers instead of a single point estimate.

3. Estimate and interpret the value of a share from the outputs of a financial statement forecast model.

  • FCFF = EBIT(1 - t) + D&A - capex - increase in NWC.
  • Terminal value: constant growth on FCFF(n+1), or an exit multiple; discount it n periods.
  • Equity value = EV - debt - preferred - NCI + cash; divide by diluted shares.
  • Terminal value often dominates; test WACC and long-run growth with sensitivity tables.
  • Scenarios with coherent assumptions show the range of value behind a recommendation.

Module at a glance

This free module has 3 lessons, 11 practice questions with full explanations.