TXN Three-Statement Model & DCF Valuation
A driver-based three-statement model and unlevered DCF valuation of Texas Instruments (TXN), built from 10-K historical data (FY2023–FY2025) with a five-year forecast to FY2030. Intrinsic value falls below current market price across the full sensitivity range, and the model surfaced that TXN's fab expansion was not self-funded from operations.
Model Preview
Full three-statement model with drivers, five-year forecast, and DCF valuation. Navigate between sheets to explore the income statement, balance sheet, cash flow statement, and WACC sensitivity table.
Business Scenario
Challenge
Build a complete three-statement model of Texas Instruments using 10-K historical data, then forecast FY2026 to FY2030 with explicit economic drivers anchored to real assumptions, not placeholders, and value the company using an unlevered DCF framework.
Solution
Linked income statement, balance sheet, and cash flow statement with every projection traced to a driver, not a hardcoded assumption. Capex steps down to reflect the tail end of TXN's fab-expansion cycle, and cash is derived as the balance sheet plug, independently verified against the cash flow statement. Valuation uses CAPM cost of equity and an unlevered DCF with a sensitivity table across WACC and terminal growth rate.
Key Findings
- Across the entire WACC × terminal growth sensitivity range, intrinsic value falls below TXN's current market price, with the gap narrowing only at the most optimistic corner of the grid. The market is pricing in a longer high-growth phase than a standard five-year perpetuity model captures.
- The linked statements surfaced a gap between operating cash flow and the combined demands of capex, dividends, and buybacks, covered by drawing down short-term investments and issuing debt. TXN's fab expansion was not self-funded from operations, a finding the income statement alone never shows.
- Assuming flat buybacks at the recent run rate drove cash negative in early forecasts. An individually plausible assumption can still be unaffordable when all other assumptions must hold simultaneously, which is the core discipline a linked model enforces.