| name | equity-research |
| description | Equity research — initiating coverage, earnings models, trading comps, and price targets.
Activate when the user mentions equity research, initiating coverage, price target,
comparable company analysis, trading comps, comp table, EV/EBITDA, P/E ratio, PEG ratio,
sum-of-the-parts, SOTP, segment valuation, equity valuation, coverage initiation,
sector analysis, industry overview, stock rating, buy/sell/hold rating, target price,
comp sheet, relative valuation, or asks about analyzing a public stock for a research
report or building an earnings model.
|
Equity Research
I produce equity research with the rigor of a senior analyst publishing under their name. Every report starts with a thesis — a clear view on why the stock is mispriced — supported by a proprietary earnings model, multiple valuation methodologies, and a defined catalyst path. The output must be specific enough to act on: a rating, a price target, and the conditions that would change both.
Scope & Boundaries
What this skill DOES:
- Initiate coverage with thesis, earnings model, valuation, and price target
- Build comparable company analysis (trading comps) with relevant peer groups
- Construct DCF and sum-of-the-parts (SOTP) valuations
- Derive price targets from multiple methodologies with probability weighting
- Analyze industry structure, competitive positioning, and secular trends
- Build quarterly and annual earnings models with driver-based projections
- Produce bull/base/bear scenario analysis with distinct price targets
- Identify catalysts and define the timeline for thesis realization
Use a different skill when:
- Hedge fund L/S with Kelly sizing and portfolio construction →
/long-short
- Writing an investment committee memo →
/investment-memo
- Post-earnings reaction and estimate revisions →
/earnings
- Credit analysis on the same company →
/credit
- Analyzing a private company →
/pe-growth or /pe-buyout
Available Tools
| Tool | Command | When to Use |
|---|
| DCF | python3 tools/dcf.py | Intrinsic value from projected free cash flows |
| WACC | python3 tools/wacc.py | Discount rate for DCF |
| IRR / NPV | python3 tools/irr.py | Expected return at current price |
| Portfolio Risk | python3 tools/portfolio_risk.py | Beta, volatility metrics |
| Kelly | python3 tools/kelly.py | Position sizing (for buy-side) |
Pre-Flight Checks
- Company: Name, ticker, sector, market cap
- Financials: Revenue, EBITDA, EPS (LTM and NTM), margins, growth rate
- Valuation: Current price, trading multiples (EV/EBITDA, P/E, EV/Revenue)
- Peer group: 4-8 comparable public companies
- Thesis direction: Bullish, bearish, or neutral — what's the variant view?
- Catalyst: What event will prove the thesis within 12-18 months?
Phase 1: Industry & Competitive Analysis
Goal: Understand the playing field before analyzing the player.
Industry Structure (Porter's Five Forces Lens)
| Force | Assessment | Impact on Company |
|-------|-----------|------------------|
| Rivalry intensity | [Low/Med/High] | [pricing power, margin pressure] |
| Threat of new entrants | [Low/Med/High] | [moat durability] |
| Buyer power | [Low/Med/High] | [pricing, switching costs] |
| Supplier power | [Low/Med/High] | [margin risk, input costs] |
| Substitution threat | [Low/Med/High] | [demand risk, disruption] |
Competitive Positioning
| Dimension | Company | Competitor A | Competitor B | Competitor C |
|-----------|---------|-------------|-------------|-------------|
| Market share | [X]% | [X]% | [X]% | [X]% |
| Revenue growth | [X]% | [X]% | [X]% | [X]% |
| Gross margin | [X]% | [X]% | [X]% | [X]% |
| R&D intensity | [X]% | [X]% | [X]% | [X]% |
| Customer NPS/retention | [X] | [X] | [X] | [X] |
| Key advantage | [describe] | [describe] | [describe] | [describe] |
Secular Trends
Tailwinds:
1. [Trend] — [X]% CAGR through [year], benefiting [segment]
2. [Trend] — regulatory/behavioral shift driving adoption
Headwinds:
1. [Trend] — [threat to growth/margins]
2. [Trend] — competitive/technology disruption risk
Phase 2: Earnings Model
Goal: Build a driver-based financial model that produces quarterly and annual projections.
Revenue Build (Top-Down + Bottom-Up Reconciliation)
Segment revenue build:
| Segment | FY-1 | FY0 | FY+1E | FY+2E | FY+3E | Driver |
|---------|------|-----|-------|-------|-------|--------|
| [Seg A] | $[X]M | $[X]M | $[X]M | $[X]M | $[X]M | [units × price / customers × ARPU] |
| [Seg B] | $[X]M | $[X]M | $[X]M | $[X]M | $[X]M | [driver] |
| [Seg C] | $[X]M | $[X]M | $[X]M | $[X]M | $[X]M | [driver] |
| **Total** | **$[X]M** | **$[X]M** | **$[X]M** | **$[X]M** | **$[X]M** | |
| YoY growth | | [X]% | [X]% | [X]% | [X]% | |
Key assumptions:
Volume growth: [X]% (driven by [market expansion / share gains / new product])
Pricing: [X]% (driven by [inflation / mix shift / new features])
FX impact: [X]% (if multinational)
Margin Trajectory
| Metric | FY-1 | FY0 | FY+1E | FY+2E | FY+3E |
|--------|------|-----|-------|-------|-------|
| Gross margin | [X]% | [X]% | [X]% | [X]% | [X]% |
| S&M % of rev | [X]% | [X]% | [X]% | [X]% | [X]% |
| R&D % of rev | [X]% | [X]% | [X]% | [X]% | [X]% |
| G&A % of rev | [X]% | [X]% | [X]% | [X]% | [X]% |
| EBITDA margin | [X]% | [X]% | [X]% | [X]% | [X]% |
| Operating margin | [X]% | [X]% | [X]% | [X]% | [X]% |
| Net margin | [X]% | [X]% | [X]% | [X]% | [X]% |
Margin bridge (FY0 → FY+2E):
Gross margin improvement: +[X]bps (mix shift / scale / procurement)
OpEx leverage: +[X]bps (revenue growing faster than headcount)
Headwinds: -[X]bps (investment in [X])
Net margin expansion: +[X]bps
EPS Build
| Metric | FY-1 | FY0 | FY+1E | FY+2E | FY+3E |
|--------|------|-----|-------|-------|-------|
| Revenue | $[X]M | | | | |
| EBITDA | $[X]M | | | | |
| D&A | ($[X]M) | | | | |
| EBIT | $[X]M | | | | |
| Interest | ($[X]M) | | | | |
| Pre-tax income | $[X]M | | | | |
| Tax rate | [X]% | | | | |
| Net income | $[X]M | | | | |
| Diluted shares | [X]M | | | | |
| **EPS** | **$[X]** | | | | |
| EPS growth | | [X]% | [X]% | [X]% | [X]% |
| Free cash flow | | | | | |
| Capex | ($[X]M) | | | | |
| FCF | $[X]M | | | | |
| FCF per share | $[X] | | | | |
| FCF yield | [X]% | | | | |
Phase 3: Comparable Company Analysis
Goal: Value the stock relative to peers on multiple metrics.
Trading Comps Table
| Company | Ticker | Mkt Cap | EV | EV/Rev NTM | EV/EBITDA NTM | P/E NTM | PEG | Rev Gr | EBITDA Mgn |
|---------|--------|---------|-----|-----------|-------------|---------|-----|--------|-----------|
| [Peer 1] | [X] | $[X]B | $[X]B | [X]x | [X]x | [X]x | [X]x | [X]% | [X]% |
| [Peer 2] | [X] | $[X]B | $[X]B | [X]x | [X]x | [X]x | [X]x | [X]% | [X]% |
| [Peer 3] | [X] | $[X]B | $[X]B | [X]x | [X]x | [X]x | [X]x | [X]% | [X]% |
| [Peer 4] | [X] | $[X]B | $[X]B | [X]x | [X]x | [X]x | [X]x | [X]% | [X]% |
| [Peer 5] | [X] | $[X]B | $[X]B | [X]x | [X]x | [X]x | [X]x | [X]% | [X]% |
|----------|-------|---------|------|-----------|-------------|---------|-----|--------|-----------|
| **Mean** | | | | [X]x | [X]x | [X]x | [X]x | [X]% | [X]% |
| **Median** | | | | [X]x | [X]x | [X]x | [X]x | [X]% | [X]% |
| **Subject** | [X] | $[X]B | $[X]B | **[X]x** | **[X]x** | **[X]x** | **[X]x** | [X]% | [X]% |
| Premium/(discount) | | | | [X]% | [X]% | [X]% | | | |
Comp Selection Criteria
Include peers that share:
- Same industry / end market exposure
- Similar revenue scale (within 0.3-3x)
- Similar growth profile (within 10pp)
- Similar margin structure
- Same geographic mix (domestic vs international)
Exclude:
- Companies undergoing M&A (distorted multiples)
- Companies with one-time events (restructuring, litigation)
- Companies with fundamentally different business models
Implied Valuation from Comps
| Methodology | Multiple | Subject Metric | Implied EV | Implied Price |
|------------|---------|---------------|-----------|--------------|
| EV/Revenue (median) | [X]x | $[X]M rev | $[X]M | $[X] |
| EV/EBITDA (median) | [X]x | $[X]M EBITDA | $[X]M | $[X] |
| P/E (median) | [X]x | $[X] EPS | — | $[X] |
| PEG-adjusted | [X]x | [X]% growth | — | $[X] |
Phase 4: DCF Valuation
Goal: Establish intrinsic value independent of market sentiment.
Run: python3 tools/dcf.py --fcf [projected_fcfs] --wacc [X] --terminal-growth [X] --net-debt [X] --shares [X]
Run: python3 tools/wacc.py --equity [X] --debt [X] --tax [X] --rf [X] --beta [X] --erp [X] --cost-of-debt [X]
WACC components:
Risk-free rate: [X]% (10Y Treasury)
Beta: [X] (2Y weekly vs S&P 500)
Equity risk premium: [X]%
Cost of equity: [X]%
Cost of debt (after-tax): [X]%
Capital weights: [X]% equity / [X]% debt
WACC: [X]%
DCF output:
PV of FCFs (explicit): $[X]M
Terminal value: $[X]M (at [X]% terminal growth)
Enterprise value: $[X]M
Less net debt: ($[X]M)
Equity value: $[X]M
Per share: $[X]
Terminal value as % of EV: [X]% (flag if >75%)
Sum-of-the-Parts (for multi-segment companies)
| Segment | Metric | Multiple | Value | Methodology |
|---------|--------|---------|-------|-------------|
| [Seg A] | $[X]M EBITDA | [X]x | $[X]M | Pure-play comp [X] trades at [X]x |
| [Seg B] | $[X]M Revenue | [X]x | $[X]M | High-growth segment, comp to [X] |
| [Seg C] | $[X]M EBITDA | [X]x | $[X]M | Mature, valued at sector median |
| Corporate costs | ($[X]M) | [X]x | ($[X]M) | Capitalized overhead drag |
| Net debt | | | ($[X]M) | |
| **Equity value** | | | **$[X]M** | |
| **Per share** | | | **$[X]** | |
Conglomerate discount: [X]% (typical: 10-25% for complex companies)
Phase 5: Price Target & Rating
Goal: Derive a defensible price target and clear rating.
Valuation Reconciliation
| Method | Weight | Value/Share | Contribution |
|--------|--------|-----------|-------------|
| DCF | [X]% | $[X] | $[X] |
| EV/EBITDA comps | [X]% | $[X] | $[X] |
| P/E comps | [X]% | $[X] | $[X] |
| SOTP | [X]% | $[X] | $[X] |
| **Blended target** | **100%** | | **$[X]** |
Scenario Analysis
| Scenario | Probability | EPS | Multiple | Price | Return |
|----------|------------|-----|---------|-------|--------|
| Bull | [X]% | $[X] | [X]x | $[X] | +[X]% |
| Base | [X]% | $[X] | [X]x | $[X] | +[X]% |
| Bear | [X]% | $[X] | [X]x | $[X] | -[X]% |
| **Probability-weighted** | 100% | | | **$[X]** | **+[X]%** |
Risk/reward: [X]:1 (upside to bull / downside to bear)
Rating Framework
| Rating | Criteria |
|--------|---------|
| Buy / Overweight | >15% upside to 12-month target, favorable risk/reward |
| Hold / Equal Weight | ±15% of target, balanced risk/reward |
| Sell / Underweight | >15% downside, unfavorable risk/reward |
Price target: $[X] — [X]% upside from current $[X]
Rating: [Buy/Hold/Sell]
Phase 6: Catalyst Path & Monitoring
Goal: Define what events will prove or disprove the thesis.
| # | Catalyst | Timeline | Probability | Impact on Price |
|---|---------|----------|------------|----------------|
| 1 | [Earnings beat / guidance raise] | [date] | [X]% | +/-[X]% |
| 2 | [Product launch / FDA approval] | [date] | [X]% | +/-[X]% |
| 3 | [Market share data point] | [date] | [X]% | +/-[X]% |
| 4 | [M&A / capital allocation] | [date] | [X]% | +/-[X]% |
| 5 | [Macro/regulatory event] | [date] | [X]% | +/-[X]% |
Thesis-killing signals:
- [Metric] deteriorates below [threshold]
- [Competitive event] occurs
- [Management action] that changes the capital allocation thesis
Quality Gates
Hard Constraints
- NEVER set a price target from a single valuation method
- NEVER use a comp table without explaining why each peer was included
- ALWAYS show the earnings model assumptions — the target means nothing without the forecast
- ALWAYS include bear case — a research report without downside analysis is advocacy, not analysis
Common Pitfalls
- Terminal value dominance — if TV is >80% of DCF value, the explicit period assumptions barely matter
- Peer group cherry-picking — including only comps that support your thesis
- Linear extrapolation — projecting current growth rate 5 years forward without modeling deceleration
- Ignoring capital allocation — buybacks, M&A, and dividends change the per-share math significantly
- Stale comps — using yesterday's multiples without adjusting for sector re-rating
Related Skills
/earnings — post-earnings analysis and estimate revisions/long-short — hedge fund thesis with position sizing/investment-memo — formal IC memo write-up/financial-statements — deep dive into the underlying financials/credit — credit perspective on the same company
