Company Valuation

Company Valuation

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

1. DCF — 5-year FCFF projection, discount at WACC, terminal value. 2. Relative — apply peer median P/E, EV/Revenue, EV/EBITDA. 3. 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.

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Step 1: Detection Flow

Detect data source and runtime deps. The skill supports 3 method paths — pick the richest one available.

Environment status:

!`python3 -c "import yfinance, numpy, pandas; print('YFIN_OK')" 2>/dev/null || echo "YFIN_MISSING"`

!`(command -v funda && funda --version) 2>/dev/null || echo "FUNDA_CLI_MISSING"`

!`python3 -c "import yfinance as yf; t=yf.Ticker('^TNX'); p=t.fast_info.last_price; print(f'RF_10Y={p/100:.4f}')" 2>/dev/null || echo "RF_FETCH_FAIL"`

Decision tree:

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

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Step 2: Choose Methods & Set Defaults

Method applicability

Defaults table

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

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

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Step 3: Pull Data

import yfinance as yf
import numpy as np
import pandas as pd

TICKER = "AAPL"  # replace
t = yf.Ticker(TICKER)

info       = t.info
income_a   = t.income_stmt
cashflow_a = t.cashflow
balance_a  = t.balance_sheet
income_q   = t.quarterly_income_stmt
cashflow_q = t.quarterly_cashflow

earnings_est = t.earnings_estimate
revenue_est  = t.revenue_estimate

price       = info.get("currentPrice") or info.get("regularMarketPrice")
market_cap  = info.get("marketCap")
shares_out  = info.get("sharesOutstanding")
total_debt  = info.get("totalDebt") or 0
cash        = info.get("totalCash") or 0
beta        = info.get("beta") or 1.0
sector      = info.get("sector")
industry    = info.get("industry")

Key financial statement rows (yfinance labels):

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Step 4: DCF Build

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

# 4a. Revenue growth path — fade from Y1 (consensus or hist CAGR) to terminal g
hist_cagr = (rev[-1] / rev[0]) ** (1 / (len(rev)-1)) - 1
y1 = float(revenue_est.loc["+1y", "growth"]) if "+1y" in revenue_est.index else hist_cagr
g_terminal = 0.025
growth_path = np.linspace(y1, g_terminal + 0.01, 5)

# 4b. Margins — 3y median
ebit_margin = float((income_a.loc["Operating Income"] / income_a.loc["Total Revenue"]).iloc[:3].median())
da_pct      = float((cashflow_a.loc["Depreciation And Amortization"] / income_a.loc["Total Revenue"]).iloc[:3].median())
capex_pct   = float((cashflow_a.loc["Capital Expenditure"].abs() / income_a.loc["Total Revenue"]).iloc[:3].median())
nwc_pct     = float((cashflow_a.loc["Change In Working Capital"].abs() / income_a.loc["Total Revenue"]).iloc[:3].median())
tax_rate    = max(0.15, min(0.30, 0.21))  # use effective if available

# 4c. FCFF per year
rev_t = [float(income_a.loc["Total Revenue"].iloc[0])]
fcff  = []
for g in growth_path:
    rev_t.append(rev_t[-1] * (1 + g))
    ebit = rev_t[-1] * ebit_margin
    nopat = ebit * (1 - tax_rate)
    fcff.append(nopat + rev_t[-1]*da_pct - rev_t[-1]*capex_pct - rev_t[-1]*nwc_pct)

# 4d. WACC
rf, erp, kd = 0.045, 0.055, 0.055  # override rf with live value from Step 1
ke = rf + beta * erp
e_v = market_cap / (market_cap + total_debt)
d_v = 1 - e_v
wacc = e_v*ke + d_v*kd*(1 - tax_rate)

# 4e. Terminal value — compute both, use midpoint
tv_gordon = fcff[-1] * (1 + g_terminal) / (wacc - g_terminal)
tv_exit   = (rev_t[-1] * ebit_margin + rev_t[-1] * da_pct) * 15  # peer median EV/EBITDA
tv_base   = 0.5 * (tv_gordon + tv_exit)

# 4f. Bridge to equity
pv_fcff = sum(f / (1+wacc)**(i+1) for i, f in enumerate(fcff))
pv_tv   = tv_base / (1+wacc)**5
ev      = pv_fcff + pv_tv
equity  = ev + cash - total_debt
implied_price_dcf = equity / shares_out

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.

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Step 5: Relative Valuation

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

PEERS = ["MSFT", "ORCL", "CRM", "NOW", "SAP", "WDAY"]  # pick by industry
multiples = {}
for p in PEERS:
    pi = yf.Ticker(p).info
    multiples[p] = {
        "pe_fwd": pi.get("forwardPE"),
        "ev_rev": pi.get("enterpriseToRevenue"),
        "ev_ebitda": pi.get("enterpriseToEbitda"),
        "ps": pi.get("priceToSalesTrailing12Months"),
    }
med_pe     = np.nanmedian([v["pe_fwd"] for v in multiples.values()])
med_ev_rev = np.nanmedian([v["ev_rev"] for v in multiples.values()])
med_ev_eb  = np.nanmedian([v["ev_ebitda"] for v in multiples.values()])

eps_ttm    = float(income_q.loc["Diluted EPS"].iloc[:4].sum())
rev_ttm    = float(income_q.loc["Total Revenue"].iloc[:4].sum())
ebitda_ttm = float(income_q.loc["EBIT"].iloc[:4].sum()) + float(cashflow_q.loc["Depreciation And Amortization"].iloc[:4].sum())
net_debt   = total_debt - cash

implied_pe       = med_pe * eps_ttm
implied_ev_rev   = (med_ev_rev * rev_ttm - net_debt) / shares_out
implied_ev_ebit  = (med_ev_eb  * ebitda_ttm - net_debt) / shares_out
implied_price_rel = np.nanmedian([implied_pe, implied_ev_rev, implied_ev_ebit])

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.

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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).

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Step 7: Triangulate, Sensitivity, Scenarios

# Blended implied price
if sotp_price is None:
    blended = 0.5*implied_price_dcf + 0.5*implied_price_rel
else:
    blended = 0.4*implied_price_dcf + 0.3*implied_price_rel + 0.3*sotp_price

# 5x5 sensitivity grid
wacc_grid = [wacc + dx for dx in (-0.01, -0.005, 0, 0.005, 0.01)]
g_grid    = [0.015, 0.020, 0.025, 0.030, 0.035]
sens = {}
for w in wacc_grid:
    for g in g_grid:
        tv = fcff[-1]*(1+g)/(w-g)
        pv = sum(f/(1+w)**(i+1) for i,f in enumerate(fcff)) + tv/(1+w)**5
        sens[(w,g)] = (pv + cash - total_debt) / shares_out

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

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Step 8: Respond to the User

Output in this order:

1. 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." 2. Snapshot — sector, industry, market cap, current price, 3M / 12M price change, LTM revenue growth. 3. Three-method summary — 3-column table: method | implied price | weight | brief rationale. 4. DCF build — assumptions table (growth path, margins, WACC components, terminal method) + 5-yr FCFF projection table + EV-to-equity bridge. 5. 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. 6. SOTP (if applicable) — segment table + adjustments + equity value. 7. Sensitivity matrix — WACC × g grid (5×5), base case highlighted. 8. Scenarios — Bull / Base / Bear table with levers + implied price. 9. Key risks — 3-5 bullets: which assumption moves the answer most; what could break the thesis.

Error handling

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

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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

Company Valuation

Estimate the intrinsic value of a public company via DCF, relative (peer multiple), and sum-of-parts (SOTP) methods, and blend into a triangulated implied share price with sensitivity tables.

What it does

• Pulls 5 years of financials + analyst estimates via yfinance
• Builds a 5-year DCF with explicit revenue / margin / WACC / terminal-value assumptions
• Applies peer median P/E, EV/Revenue, EV/EBITDA multiples across 4-6 peers
• Runs SOTP when the company has 2+ distinct reporting segments
• Presents a blended implied price with method weights, WACC × g sensitivity matrix, and Bull/Base/Bear scenarios
• Handles banks/REITs/pre-revenue/cyclical edge cases with appropriate fallbacks

Triggers

what is AAPL worth, valuation of NVDA, fair value of TSLA, DCF for MSFT, build a DCF, intrinsic value, implied share price, is X overvalued/undervalued, relative valuation, EV/EBITDA target, SOTP, sum of the parts, price target from fundamentals, value this company

Prerequisites

• Python 3.8+
• yfinance, numpy, pandas (auto-installed if missing)

Optional: finance-data-providers:funda-data skill as a fallback data source.

Platform

CLI-based agents (Claude Code). Requires shell + pip.

Setup

No authentication required. First run will auto-install dependencies.

Reference Files

• references/dcf.md — DCF methodology, industry-specific guidance (software, retail, financials, healthcare, energy, manufacturing, CPG, telecom, REITs, streaming), common pitfalls
• references/relative_valuation.md — Peer selection heuristics, multiple adjustment rules, Rule of 40 for SaaS, default peer sets by theme
• references/sotp.md — Sum-of-parts methodology, conglomerate discount detection, catalyst framework, position sizing
• references/wacc_erp_rates.md — Risk-free rates (live + default), equity risk premiums, sector WACC bands, sector-default betas, terminal growth ceilings

Output

Structured briefing with: headline verdict, snapshot, three-method summary, DCF build, peer comparison, SOTP (if applicable), sensitivity matrix, scenarios, key risks, and caveats.

Disclaimer

For research and educational purposes only. Not financial advice.

DCF Methodology — Detailed Reference

Expands on the summary in SKILL.md. Use this when building the DCF build table or when the user asks for industry-specific treatment.

When DCF Is Appropriate

Good fit:

• Mature companies with predictable cash flows
• Companies whose revenue and margin trajectory can be estimated within a reasonable confidence band
• Strategic valuations requiring intrinsic value assessment
• Cross-checking a relative valuation

Poor fit:

• Pre-revenue / early-stage (no cash flow history)
• Banks, insurance (use DDM or excess return model)
• REITs (use NAV)
• Highly cyclical businesses without a clear cycle baseline — use mid-cycle earnings instead

Projection Model (5-Year Explicit Forecast)

Revenue projection

1. Compute historical 3–5 year CAGR. 2. Pull analyst consensus from yfinance.Ticker.revenue_estimate. 3. Consider industry growth, competitive position, and company guidance. 4. Project revenue for Y1–Y5, fading linearly toward terminal growth rate.

Revenue_t = Revenue_{t-1} × (1 + g_t)

EBIT and Free Cash Flow Build

Revenue
- COGS                          → historical gross margin trend
= Gross Profit
- SG&A                          → historical SG&A % of revenue
- R&D                           → historical R&D % of revenue
- Other OpEx
= EBIT (Operating Income)

FCFF = EBIT × (1 − Tax Rate)
     + Depreciation & Amortization
     + Stock-Based Compensation    ← only if treating SBC as non-cash
     − Capital Expenditures
     − Change in Net Working Capital

Assumption checklist (state explicitly)

WACC Calculation

WACC = (E/V) × Ke + (D/V) × Kd × (1 − Tax Rate)

Cost of Equity (CAPM)

Ke = Risk-Free Rate + Beta × Equity Risk Premium + Size Premium (if applicable)

Cost of Debt

• Preferred: interest expense / total debt from financials.
• Fallback: credit rating spread over risk-free rate.
• Investment-grade: 4–6%. High-yield: 7–10%.

Capital structure

Use market values:

• E = market cap
• D = total debt (balance sheet)
• V = E + D

Terminal Value

Method 1: Perpetuity Growth (Gordon Growth)

TV = FCFF_5 × (1 + g) / (WACC − g)

• Terminal growth g: 2–3% typical; must not exceed long-term GDP (~2.5% US, ~3–4% EM).
• TV normally represents 60–80% of total EV. Flag if outside that range.

Method 2: Exit Multiple

TV = EBITDA_5 × exit EV/EBITDA multiple

• Use current peer trading multiples as reference.
• Apply discount for growth deceleration by Y5.
• Cross-check against Gordon TV — if they diverge by >30%, reconcile assumptions.

Bridge to Equity Value

PV of FCFF = Σ FCFF_t / (1 + WACC)^t  for t = 1..5
PV of TV   = TV / (1 + WACC)^5

Enterprise Value = PV of FCFF + PV of TV
+ Cash & equivalents
− Total debt
− Minority interest
− Preferred stock
+ Equity investments (if material)
= Equity Value

Implied share price = Equity Value / diluted shares outstanding

Sensitivity & Scenarios

WACC × Terminal Growth matrix

5×5 grid. Vary WACC by ±1% in 0.5% steps and g by 0.5% from 1.5% to 3.5%. Highlight base case.

Scenario analysis

Industry-Specific Guidance

Technology / SaaS

• EV/Revenue often more meaningful than P/E if not yet profitable.
• Key metrics: ARR growth, net dollar retention (NRR), Rule of 40 (growth% + FCF margin ≥ 40).
• CapEx light (3–8% rev); R&D heavy (15–30%).
• SBC material — decide cash vs non-cash upfront and disclose.
• Terminal growth: 3–4% for category leaders, 2–3% others.

Retail / E-commerce

• Revenue = same-store sales growth + new store openings (physical) OR GMV growth (digital).
• Working capital matters: inventory turns, payables.
• Split CapEx: maintenance (existing) vs growth (new stores/fulfillment).
• Normalize for one-time charges (store closures, write-downs).

Financial Services (Banks / Insurance)

• Standard DCF is wrong. Use DDM or excess return model.
• If forced: project NII, provisions, non-interest income separately.
• Discount rate = cost of equity only (debt is operational).

Healthcare / Pharma

• Separate existing portfolio from pipeline.
• Key risk: patent cliffs, FDA approval probability.
• R&D: 15–25% of revenue.
• Biotech: risk-adjust pipeline NPV by phase success probability.

Energy (Oil & Gas)

• Revenue tied to commodity prices — use strip pricing or scenarios.
• High CapEx; distinguish development vs exploration.
• Depletion accounting differs from standard D&A.
• Terminal value very sensitive to long-term price deck.

Manufacturing / Industrial

• Cyclical — use mid-cycle earnings for normalization.
• CapEx 8–15% of revenue.
• Working capital swings with cycle — use through-cycle averages.
• WACC 8–11% typical.

Consumer Goods (CPG)

• Stable, predictable — good DCF candidates.
• Distinguish organic vs M&A growth.
• Watch gross margin trends, A&P spend, input costs.
• Terminal growth 2–3% (population + inflation).

Telecommunications

• High CapEx (15–25%) for network buildout.
• Recurring revenue, low churn — good for DCF.
• Spectrum costs lumpy.
• WACC 7–9% for large incumbents.

Real Estate / REITs

• Use NAV as primary; DCF supplementary.
• Project NOI instead of FCF.
• Cap rate replaces WACC at property level.
• Distinguish maintenance vs growth CapEx.

Media / Streaming

• Subscriber growth × ARPU drives revenue.
• Content spend dominant cost — capitalize vs expense debate matters.
• Path to profitability > current margin for growth-stage.
• High operating leverage at scale.

Common Pitfalls

• Terminal value dominance: If TV > 80% of EV, model is really a multiple-expansion bet. Disclose.
• Growth > WACC: Breaks Gordon formula. Cap g below WACC.
• Inconsistent tax rates: Historical effective rate may include one-offs. Cross-check with statutory.
• Double-counting SBC: Either subtract SBC from FCFF OR use diluted shares that price it in — not both, and not neither.
• Stale beta: yfinance beta may be 5-year or 3-year. For recent IPOs or post-restructuring businesses, compute fresh.
• Ignoring minority interest / preferred: These are claims on EV ahead of common equity. Always subtract.
• Circular WACC: WACC uses market cap → which is what we're trying to estimate. For IPOs or controversial names, iterate or use target capital structure.

Relative Valuation — Detailed Reference

Relative valuation implies a price by applying peer multiples. Fast, market-anchored, and captures sentiment — but "garbage in, garbage out" when peers are poorly chosen.

Peer Selection Heuristics

Aim for 4–6 peers. More is noisier, fewer is brittle.

Avoid: Mega-cap diversified companies as peers for pure-play small/mid-caps (e.g., MSFT is not a good peer for DDOG).

Multiples Cheat Sheet

Computing Implied Price

For each multiple, take peer median (not mean — medians are robust to outliers).

# Equity multiples
Implied price (P/E) = peer median P/E × target EPS_TTM

# Enterprise multiples
Implied EV (EV/Rev)   = peer median EV/Rev × target Revenue_TTM
Implied EV (EV/EBITDA)= peer median EV/EBITDA × target EBITDA_TTM

Net debt = Total Debt − Cash
Implied equity value = Implied EV − Net debt − Minority interest − Preferred
Implied price = Implied equity value / diluted shares

Adjustments — When NOT to Apply Peer Median Blindly

Adjust ±10–30% based on target vs peer median:

Always state the adjustment and the reason.

Rule of 40 for SaaS

For software/SaaS peers, add Rule of 40 as a supplementary anchor:

Rule of 40 = Revenue Growth % + FCF Margin %

Common Peer Sets (Fallback)

Hardcoded starter sets when industry classification is ambiguous. Expand as needed.

Cross-Check: Target vs Peers Table

Always produce a table of peers with:

• Ticker / name
• Market cap
• Revenue growth (LTM, forward)
• Gross margin, EBITDA margin, operating margin
• P/E (fwd), EV/Revenue, EV/EBITDA
• Peer median (bottom row)

This lets the user see at a glance whether the target "deserves" a premium/discount.

Common Pitfalls

• Using a single multiple: Triangulate with ≥2 multiples. EV/EBITDA should agree with EV/Revenue within ±15% when applied to same peer set.
• Outlier peers: Exclude if P/E > 100 or EV/Rev > 50 unless target is similarly extreme.
• Peer in trough: If peer is in distress or restructuring, their multiple compresses — excluding them or adjusting.
• Different fiscal year ends: Normalize to TTM.
• Stock-based comp: EV/EBITDA without SBC adjustment overstates multiples for SaaS. Consider EV/EBITDA (ex-SBC) for SaaS peers.
• Currency: International peers — normalize to USD and note FX sensitivity.

Sum-of-the-Parts (SOTP) Valuation

For companies with 2+ reporting segments, SOTP values each segment using pure-play peer multiples, sums them, and compares to market cap to detect conglomerate discount.

When to Use SOTP

Triggers:

• Company has 2+ reportable operating segments in 10-K / 20-F
• Segments operate in materially different industries (e.g., tech + retail, media + theme parks)
• One segment appears to grow faster or be more valuable than blended multiple suggests
• SOTP analysis suggests >20% upside vs current market cap (meaningful conglomerate discount)
• Plausible catalyst within 12-24 months: activist, strategic review, rumored spin-off, board pressure

Do not force SOTP when:

• Segments share heavy operational integration (e.g., vertically integrated manufacturers) — synergies would be destroyed by separation
• Segment disclosures are too coarse to model independently
• No realistic path to value realization (management opposed, no activists)

Workflow

Step 1: Extract Segment Financials

From latest 10-K / 10-Q segment disclosure, pull per segment:

• Revenue
• Operating income (EBIT)
• EBITDA (if disclosed, else EBIT + allocated D&A)
• Revenue growth YoY
• Operating margin

Track inter-segment eliminations and unallocated corporate expenses separately.

Step 2: Identify Pure-Play Peers

For each segment, find 3-5 listed pure-play peers in the same industry. Examples:

Record peer median EV/EBITDA, EV/Revenue (for growth segments), and P/E.

Step 3: Apply Multiples

segment_EV_i = segment_EBITDA_i × peer_median_EV/EBITDA_i

Use EV/EBITDA as default. For high-growth or pre-profit segments, use EV/Revenue.

Step 4: Adjust for Corporate-Level Items

Total EV from segments
− Unallocated corporate costs (cap at 2-5% of revenue, or discount at 8x the ongoing cost)
− Minority interest
− Total debt
− Preferred stock
− Pension underfunding
+ Cash & equivalents
+ Non-operating assets (excess real estate, investments, NOLs)
= Equity Value

Implied price = Equity Value / diluted shares

Step 5: Compute Conglomerate Discount

discount_pct = (SOTP_price − market_price) / SOTP_price × 100

Thresholds:

• >30%: compelling; likely actionable
• 20-30%: meaningful; need catalyst
• 10-20%: narrow; requires catalyst + technicals
• <10%: no opportunity

Step 6: Identify Catalyst

Conglomerate discount can persist indefinitely without a catalyst. Require at least one of:

• Activist investor filed 13D pushing for breakup
• Management publicly discussed "strategic alternatives" or "portfolio simplification"
• Rumored or announced spin-off / divestiture
• CEO change (new CEOs often simplify)
• Peer transaction highlighting valuation gap
• Board refresh with activist nominees

Example

DiverseTech Corp (DVTK) — two segments:

• Cloud Platform: $3B rev, 30% growth, 25% EBITDA margin → $0.75B EBITDA
• Legacy Hardware: $5B rev, flat, 15% EBITDA margin → $0.75B EBITDA

Peer multiples:

• Cloud peers median EV/EBITDA: 20x → cloud EV = $15B
• Hardware peers median EV/EBITDA: 8x → hardware EV = $6B

Total segment EV = $21B
− Corporate costs  = $2B
− Net debt         = $2B
= Equity value     = $17B
Shares out         = 250M
Implied SOTP price = $68
Market price       = $42
Discount           = 38% — compelling

Catalyst: Activist filed 13D demanding cloud spin-off. Enter position at $42.

Edge Cases & Traps

Position Sizing (if SOTP feeds into a trade)

• 4-6% of portfolio per SOTP position (value trades with identified catalyst)
• Stop-loss: −15% from entry (wider stop because discount can widen before closing)
• Time stop: 12 months with no catalyst progress → reassess
• Portfolio cap: 15% of capital in SOTP / conglomerate-discount trades (correlated risk)
• Trim when discount narrows to <10%; add when it widens to >35% with no thesis break

Performance Expectations

• Win rate with catalyst: 55-65%
• Win rate without catalyst: 40-45%
• Average winner: +20% to +40% over 12-24 months
• Average loser: −10% to −15%
• Risk/reward with catalyst: 2:1 to 3:1

WACC, ERP, Risk-Free Rates & Sector Benchmarks

Reference values for cost-of-capital inputs. Prefer live values over these defaults when available.

Risk-Free Rate

Use the 10-year sovereign yield of the company's reporting currency.

Live fetch:

import yfinance as yf
rf = yf.Ticker("^TNX").fast_info.last_price / 100

Default (when fetch fails): rf = 0.045 (4.5%). Flag as stale.

Equity Risk Premium (ERP)

Use Damodaran's monthly ERP update (damodaran.nyu.edu) as anchor. Intra-year, 5.5% is a reasonable mid-range.

Adjust with country risk premium (CRP) for emerging markets:

ERP_country = ERP_mature + CRP

Cost of Debt

Preferred: interest_expense / total_debt from financial statements.

Fallback: credit rating spreads over risk-free rate.

Default (when unknown): kd = 0.055 for large-caps, 0.07 for mid-caps.

Levered Beta Defaults (by sector)

Use when yfinance returns None or an implausible value (e.g., beta < 0 for a non-gold stock).

Source: Damodaran industry betas (levered, US-listed, recent year-end update).

WACC Sanity Ranges by Sector

If computed WACC falls outside these bands, double-check inputs (beta, capital structure, kd).

Size Premium (CRSP / Ibbotson style)

Small / micro caps justify additional return above CAPM. Add to ke if applicable.

Terminal Growth Rate Ceilings

Terminal g must be plausible relative to long-run nominal GDP growth. Hard ceilings:

Global-franchise exporters can argue slightly above local GDP, but rarely above +0.5%.

Cross-Check: Implied Cost of Equity

Back-solve from current multiples to sanity-check WACC:

Forward earnings yield ≈ 1 / forward P/E
Implied ke ≈ earnings yield + sustainable growth

If computed WACC diverges from this implied number by >300bps, one of the inputs (beta, ERP, growth) is off.