| name | financial-analysis-dcf |
| description | DCF (Discounted Cash Flow) valuation for US stocks using SEC EDGAR financials. Use when asked to: estimate intrinsic value or fair value of a US stock; determine if a stock is overvalued or undervalued; run a discounted cash flow analysis; calculate upside/downside from current price. Triggers: "what is AAPL worth", "DCF MSFT", "is NVDA overvalued", "intrinsic value of GOOGL", "fair value Tesla".
|
DCF Valuation
Estimate intrinsic value per share using a discounted cash flow model. Data from SEC EDGAR (financials), FRED (risk-free rate), and Yahoo Finance (price, beta).
Setup
No dependencies required. All scripts use Python standard library only.
Workflow
Step 1 — Run the DCF script
bash run.sh <SYMBOL>
bash run.sh <SYMBOL> --terminal-growth 3.0 --fcf-growth 15 --projection-years 7
The script:
- Fetches 5 years of 10-K data from SEC EDGAR
- Computes unlevered FCF = OCF − CapEx + InterestExpense × (1−T)
- Derives historical FCF growth rate (or uses override)
- Gets risk-free rate from FRED (10Y Treasury)
- Gets beta and current price from Yahoo Finance
- Calculates WACC = Ke × E/V + Kd × (1−T) × D/V
- Projects FCFs, computes terminal value (Gordon Growth Model)
- Generates 5×5 sensitivity table (WACC vs terminal growth)
Step 2 — Section 1: Summary
First output must be this summary box:
[TICKER] — DCF VALUATION
Intrinsic value: $XXX.XX | Current price: $XXX.XX | ▲/▼ XX.X%
WACC: X.X% | Terminal growth: X.X% | FCF base: $X.XB
Step 3 — Section 2: Sensitivity Table
Show the full 5×5 sensitivity table from the JSON output:
Terminal Growth \\ WACC | 8.2% | 9.2% | 10.2%
------------------------|---------|---------|--------
1.5% | $198.4 | $176.2 | $158.1
2.5% | $221.3 | $194.5 | $172.6
3.5% | $251.7 | $218.0 | $191.4
Display N/A for null values (WACC ≤ terminal growth).
Step 4 — Section 3: Interpretation
Note key assumptions and their impact:
- Which inputs drive the most variance (usually WACC and growth rate)
- Whether the beta seems reasonable for the company
- How the historical FCF growth rate compares to analyst expectations
- Any red flags (negative FCF years, volatile cash flows, high debt)
Disclaimer: DCF output is highly sensitive to WACC and growth assumptions. It should be used as one input among many, not as a definitive price target. Always present the sensitivity table alongside the point estimate.
Model Assumptions
- ERP: 5.5% (Damodaran market average)
- Tax rate: derived from SEC filings (IncomeTaxExpense / PreTaxIncome); fallback 21%
- Cost of debt: derived from SEC filings (InterestExpense / LongTermDebt); fallback 4%
- FCF: Unlevered = OCF − CapEx + InterestExpense × (1−T) from most recent 10-K
- FCF growth: per-share UFCF CAGR from historical 10-K data (accounts for buybacks); fallback 3% if insufficient data
- Beta: OLS regression on daily returns vs SPY (~5 years); Blume adjustment applied (adjusted = 0.67 × raw + 0.33)
- Shares outstanding: from SEC EDGAR; fallback to market cap / price
- Mid-year convention: FCFs and terminal value both discounted at mid-year
Formatting Rules
- Intrinsic value and current price: "$XXX.XX"
- Upside/downside: "▲ +XX.X%" or "▼ −XX.X%"
- WACC and growth rates: one decimal, e.g. "9.2%"
- FCF: B or M, e.g. "$12.3B"
When NOT to Use
- Negative or volatile FCF: companies with negative free cash flow cannot be valued via DCF — the model requires a positive base FCF to project forward
- Banks and financial institutions: revenue and cash flow structures differ fundamentally (interest income vs. operating revenue); use price-to-book or dividend discount models instead
- Insurance companies: similar to banks — earnings driven by underwriting and investment income, not operating cash flow
- Pre-revenue or early-stage companies: no meaningful FCF history to extrapolate
Limitations
- US stocks only: SEC EDGAR data for US-listed equities
- Backward-looking: uses historical financials — future may differ significantly
- No analyst estimates: growth rates extrapolated from historical data unless user provides one
