company-valuation

Company Valuation

Triangulates intrinsic value via three methods, then blends them to an implied share price:

DCF — 5-year FCFF projection, discount at WACC, terminal value.
Relative — apply peer median P/E, EV/Revenue, EV/EBITDA.
SOTP — when 2+ distinct reporting segments exist, value each at pure-play peer multiples.

Always present a WACC × terminal-growth sensitivity table and Bull/Base/Bear scenarios.

Disclaimer: Research/educational output. Not financial advice.

Step 1: Detection Flow

Detect data source and runtime deps. The skill supports 2 method paths — pick the richest one available.

Environment status:

!`python3 -c "exec('try:\n import yfinance, numpy, pandas\n print(\'YFIN_OK\')\nexcept Exception:\n print(\'YFIN_MISSING\')')"`

!`python3 -c "exec('try:\n import yfinance as yf\n t=yf.Ticker(\'^TNX\')\n p=t.fast_info.last_price\n print(f\'RF_10Y={p/100:.4f}\')\nexcept Exception:\n print(\'RF_FETCH_FAIL\')')"`

Decision tree:

Condition	Method path
`YFIN_OK`	Path A (primary): yfinance for financials + peer multiples
`YFIN_MISSING`	Path B: pip-install yfinance, then Path A. `python3 -m pip install -q yfinance numpy pandas`
`RF_FETCH_FAIL`	Use default `rf = 0.045` and note stale risk-free rate in output

If RF_10Y= printed, use that value as rf in Step 4d instead of the hardcoded 4.5%.

Step 2: Choose Methods & Set Defaults

Method applicability

Company type	DCF	Relative	SOTP	Fallback
Mature cash-flow (CPG, telecom, utilities)	✅ primary	✅	❌	—
High-growth SaaS / software	✅ with care	✅ primary	❌	Use EV/Revenue + Rule of 40
Multi-segment conglomerate	✅	✅	✅ primary	See `references/sotp.md`
Banks / insurance	❌	✅ (P/B, P/TBV)	❌	DDM or excess return; note in output
Pre-revenue	❌	EV/Revenue only	❌	Flag low confidence
REITs	❌	✅ (P/FFO, P/AFFO)	❌	NAV-based
Cyclicals (energy, semis, industrials)	✅ on mid-cycle	✅	sometimes	Normalize through-cycle

Defaults table

Every parameter below MUST have a value before moving to Step 3. Use these unless the user overrides.

Parameter	Default	Rationale
Projection horizon	5 years	Standard explicit forecast window
Terminal growth `g`	2.5%	~ long-run US GDP
Risk-free rate `rf`	Live 10Y UST from Step 1, else 4.5%	Current cost of capital anchor
Equity risk premium `erp`	5.5%	Damodaran mid-range
Beta	`info['beta']` from yfinance	Market-observed levered beta
Cost of debt `kd`	`interest_expense / total_debt`, else 5.5%	Effective rate; fallback to IG spread
Tax rate	3-yr median effective rate, floored 15%, capped 30%	Strips out one-offs
Margin assumptions	3-yr median of each ratio	Smooths cyclical noise
SBC treatment	Cash for software/SaaS; non-cash for industrials/CPG	Industry convention
Peer count	4-6	Balances signal vs noise
Peer multiple	Median (not mean)	Robust to outliers
Method weights (no SOTP)	DCF 50% / Relative 50%	Equal triangulation
Method weights (with SOTP)	DCF 40% / Relative 30% / SOTP 30%	SOTP gets weight when applicable
Sensitivity grid	WACC ±1% in 0.5% steps × g from 1.5-3.5% in 0.5%	5×5 matrix

See references/wacc_erp_rates.md for current risk-free rates, ERP tables, and sector WACC benchmarks.

Step 3: Pull Data

import yfinance

Key financial statement rows (yfinance labels):

Need	Row
Revenue	`Total Revenue`
EBIT	`Operating Income`
Net income	`Net Income`
D&A	`Depreciation And Amortization` (in cashflow)
CapEx	`Capital Expenditure` (negative)
ΔNWC	`Change In Working Capital` (cashflow)
SBC	`Stock Based Compensation` (cashflow)

Step 4: DCF Build

Full methodology + industry-specific tweaks in references/dcf.md. Quick skeleton:

Gates: (a) if wacc <= g_terminal → stop, g too aggressive; (b) if pv_tv / ev > 0.85 or < 0.45 → flag and show both TV methods; (c) if wacc is outside the sector sanity band in references/wacc_erp_rates.md → note.

Step 5: Relative Valuation

Select 4-6 peers. Peer map and adjustment rules in references/relative_valuation.md.

Adjust peer median ±10-30% if target's growth or margin profile diverges materially. Always state the adjustment and reason. Rule of 40 anchor for SaaS in references/relative_valuation.md.

Step 6: SOTP (multi-segment only)

Skip unless the 10-K reports 2+ operating segments with distinct economics. yfinance does NOT expose segment data — user must supply or parse from filings. Full methodology in references/sotp.md:

Identify segments + pure-play peer for each
Apply peer median EV/EBITDA (or EV/Rev for growth segments)
Subtract unallocated corporate costs (cap 2-5% of revenue if unknown)
Subtract net debt, minority interest; divide by shares

SOTP discount = (SOTP price − market price) / SOTP price. Flag if >20% (conglomerate discount).

Step 7: Triangulate, Sensitivity, Scenarios

Also produce Bull / Base / Bear: shift revenue growth ±300bps, EBIT margin ±200bps, WACC ∓100bps, terminal g 3.0% / 2.5% / 1.5%.

Step 8: Respond to the User

Output in this order:

Headline verdict — one sentence: blended fair value, vs. current, % upside/downside, most bullish/bearish method. Example: "AAPL fair value ≈ $215 (blended), vs. current $198 → ~9% upside; DCF is most bullish at $228."
Snapshot — sector, industry, market cap, current price, 3M / 12M price change, LTM revenue growth.
Three-method summary — 3-column table: method | implied price | weight | brief rationale.
DCF build — assumptions table (growth path, margins, WACC components, terminal method) + 5-yr FCFF projection table + EV-to-equity bridge.
Peer comparison — table of peers with P/E fwd, EV/Rev, EV/EBITDA, gross margin, rev growth; bottom row = median; flag target's premium/discount.
SOTP (if applicable) — segment table + adjustments + equity value.
Sensitivity matrix — WACC × g grid (5×5), base case highlighted.
Scenarios — Bull / Base / Bear table with levers + implied price.
Key risks — 3-5 bullets: which assumption moves the answer most; what could break the thesis.

Error handling

Missing / edge case	Action
yfinance returns `None` for beta	Use sector-default beta from `references/wacc_erp_rates.md`
Negative LTM EBITDA	Skip EV/EBITDA multiple; rely on EV/Revenue + DCF
Negative LTM EPS	Skip P/E multiple; use forward P/E if positive, else skip
Growth > WACC in Gordon	Cap `g = wacc − 0.5%` and flag
Fewer than 3 years history	Use what's available; flag data confidence as "low"
Peer data fetch fails	Drop that peer from median; note in output
No segment data for SOTP	Skip Section 6; proceed with DCF + Relative only

Caveats to include

TTM data lags real-time; peer multiples reflect market sentiment (can overshoot)
DCF is garbage-in/garbage-out; sensitivity matters more than a point estimate
yfinance data is unofficial; cross-check any decision with primary filings
Not financial advice

Reference Files

references/dcf.md — DCF methodology + industry-specific guidance (software, retail, financials, healthcare, energy, manufacturing, CPG, telecom, REITs, streaming)
references/relative_valuation.md — Peer selection, multiple adjustment rules, Rule of 40, peer sets by theme
references/sotp.md — Sum-of-parts methodology, conglomerate discount detection, catalysts
references/wacc_erp_rates.md — Risk-free rates, equity risk premiums, sector WACC benchmarks, sector-default betas