Financial Analysis. Lesson 21. Financial Modeling and Forecasting Techniques

Financial Analysis. Lesson 21. Financial Modeling and Forecasting Techniques

  1. Financial modeling creates quantitative representations of a company’s financial situation.

  2. Three-statement model links income statement, balance sheet, and cash flow statement.

  3. Discounted cash flow (DCF) model estimates company value using projected cash flows.

  4. LBO model simulates leveraged buyouts by modeling debt and equity returns.

  5. Sensitivity analysis tests model outcomes by adjusting individual variables.

  6. Scenario analysis explores outcomes under varied economic and business scenarios.

  7. Comparable company analysis (CCA) values firms based on industry peers' metrics.

  8. Revenue modeling forecasts future sales based on historical and market data.

  9. Expense forecasting estimates future costs using trends and operational insights.

  10. Growth rate assumptions project revenue or expenses based on historical patterns.

  11. Terminal value represents the future worth of a company in perpetuity.

  12. EBITDA multiple estimates enterprise value based on industry-standard EBITDA ratios.

  13. Capital expenditure (CapEx) forecast projects investments in long-term assets.

  14. Depreciation schedule calculates asset depreciation impacting cash flows over time.

  15. Working capital forecast predicts cash needs for short-term obligations.

  16. Net operating profit after tax (NOPAT) measures core business profitability.

  17. Equity bridge shows changes from net income to shareholders’ equity.

  18. Debt schedule details interest and principal payments affecting cash flows.

  19. Dividend forecast estimates future payouts to shareholders in financial models.

  20. Cash flow waterfall outlines cash distribution across debt, equity, and reserves.


Technical Examples:

  1. DCF model assists in determining intrinsic company value based on projections.

  2. Three-statement model links financial statements to maintain balance and accuracy.

  3. Sensitivity analysis tests model reliability under varying input assumptions.