DCF Model Builder

Overview

This skill creates institutional-quality DCF models for equity valuation following investment banking standards. Each analysis produces a detailed Excel model (with sensitivity analysis included at the bottom of the DCF sheet).

Tools

• Default to using all of the information provided by the user and MCP servers available for data sourcing.

Critical Constraints - Read These First

These constraints apply throughout all DCF model building. Review before starting:

Environment: Office JS vs Python/openpyxl:

• If running inside Excel (Office Add-in / Office JS environment): Use Office JS directly — do NOT use Python/openpyxl. Write formulas via range.formulas = [["=D19*(1+$B$8)"]]. No separate recalc step needed; Excel calculates natively. Use range.format.* for styling. The same formulas-over-hardcodes rule applies: set .formulas, never .values for derived cells.
• If generating a standalone .xlsx file (no live Excel session): Use Python/openpyxl as described below, then run recalc.py before delivery.
• The rest of this skill uses openpyxl examples — translate to Office JS API calls when in that environment, but all principles (formula strings, cell comments, section checkpoints, sensitivity table loops) apply identically.

⚠️ Office JS merged cell pitfall: When building section headers with merged cells, do NOT call .merge() then set .values on the merged range — Office JS still reports the range's original dimensions and will throw InvalidArgument: The number of rows or columns in the input array doesn't match the size or dimensions of the range. Instead, write the value to the top-left cell alone, then merge and format the full range:

// WRONG — throws InvalidArgument:
const hdr = ws.getRange("A7:H7");
hdr.merge();
hdr.values = [["MARKET DATA & KEY INPUTS"]];  // 1×1 array vs 1×8 range → fails

// CORRECT — value first on single cell, then merge + format the range:
ws.getRange("A7").values = [["MARKET DATA & KEY INPUTS"]];
const hdr = ws.getRange("A7:H7");
hdr.merge();
hdr.format.fill.color = "#1F4E79";
hdr.format.font.bold = true;
hdr.format.font.color = "#FFFFFF";

This applies to every merged section header in the DCF (market data, scenario blocks, cash flow projection, terminal value, valuation summary, sensitivity tables).

Formulas Over Hardcodes (NON-NEGOTIABLE):

• Every projection, margin, discount factor, PV, and sensitivity cell MUST be a live Excel formula — never a value computed in Python and written as a number
• When using openpyxl: ws["D20"] = "=D19*(1+$B$8)" is correct; ws["D20"] = calculated_revenue is WRONG
• The only hardcoded numbers permitted are: (1) raw historical inputs, (2) assumption drivers (growth rates, WACC inputs, terminal g), (3) current market data (share price, debt balance)
• If you catch yourself computing something in Python and writing the result — STOP. The model must flex when the user changes an assumption.

Verify Step-by-Step With the User (DO NOT build end-to-end):

• After data retrieval → show the user the raw inputs block (revenue, margins, shares, net debt) and confirm before projecting
• After revenue projections → show the projected top line and growth rates, confirm before building margin build
• After FCF build → show the full FCF schedule, confirm logic before computing WACC
• After WACC → show the calculation and inputs, confirm before discounting
• After terminal value + PV → show the equity bridge (EV → equity value → per share), confirm before sensitivity tables
• Catch errors at each stage — a wrong margin assumption discovered after sensitivity tables are built means rebuilding everything downstream

Sensitivity Tables:

• Use an ODD number of rows and columns (standard: 5×5, sometimes 7×7) — this guarantees a true center cell
• Center cell = base case. Build the axis values so the middle row header and middle column header exactly equal the model's actual assumptions (e.g., if base WACC = 9.0%, the middle row is 9.0%; if terminal g = 3.0%, the middle column is 3.0%). The center cell's output must therefore equal the model's actual implied share price — this is the sanity check that the table is built correctly.
• Highlight the center cell with the medium-blue fill (#BDD7EE) + bold font so it's immediately visible which cell is the base case.
• Populate ALL cells (typically 3 tables × 25 cells = 75) with full DCF recalculation formulas
• Use openpyxl loops (or Office JS loops) to write formulas programmatically
• NO placeholder text, NO linear approximations, NO manual steps required
• Each cell must recalculate full DCF for that assumption combination

Cell Comments:

• Add cell comments AS each hardcoded value is created
• Format: "Source: [System/Document], [Date], [Reference], [URL if applicable]"
• Every blue input must have a comment before moving to next section
• Do not defer to end or write "TODO: add source"

Model Layout Planning:

• Define ALL section row positions BEFORE writing any formulas
• Write ALL headers and labels first
• Write ALL section dividers and blank rows second
• THEN write formulas using the locked row positions
• Test formulas immediately after creation

Formula Recalculation:

• Run python recalc.py model.xlsx 30 before delivery
• Fix ALL errors until status is "success"
• Zero formula errors required (#REF!, #DIV/0!, #VALUE!, etc.)

Scenario Blocks:

• Create separate blocks for Bear/Base/Bull cases
• Show assumptions horizontally across projection years within each block
• Use IF formulas: =IF($B$6=1,[Bear cell],IF($B$6=2,[Base cell],[Bull cell]))
• Verify formulas reference correct scenario block cells

DCF Process Workflow

Step 1: Data Retrieval and Validation

Fetch data from MCP servers, user provided data, and the web.

Data Sources Priority:

1. MCP Servers (if configured) - Structured financial data from providers like Daloopa
2. User-Provided Data - Historical financials from their research
3. Web Search/Fetch - Current prices, beta, debt and cash when needed

Validation Checklist:

• Verify net debt vs net cash (critical for valuation)
• Confirm diluted shares outstanding (check for recent buybacks/issuances)
• Validate historical margins are consistent with business model
• Cross-check revenue growth rates with industry benchmarks
• Verify tax rate is reasonable (typically 21-28%)

Step 2: Historical Analysis (3-5 years)

Analyze and document:

• Revenue growth trends: Calculate CAGR, identify drivers
• Margin progression: Track gross margin, EBIT margin, FCF margin
• Capital intensity: D&A and CapEx as % of revenue
• Working capital efficiency: NWC changes as % of revenue growth
• Return metrics: ROIC, ROE trends

Create summary tables showing:

Historical Metrics (LTM):
Revenue: $X million
Revenue growth: X% CAGR
Gross margin: X%
EBIT margin: X%
D&A % of revenue: X%
CapEx % of revenue: X%
FCF margin: X%

Step 3: Build Revenue Projections

Methodology:

1. Start with latest actual revenue (LTM or most recent fiscal year)
2. Apply growth rates for each projection year
3. Show both dollar amounts AND calculated growth %

Growth Rate Framework:

• Year 1-2: Higher growth reflecting near-term visibility
• Year 3-4: Gradual moderation toward industry average
• Year 5+: Approaching terminal growth rate

Formula structure:

• Revenue(Year N) = Revenue(Year N-1) × (1 + Growth Rate)
• Growth %(Year N) = Revenue(Year N) / Revenue(Year N-1) - 1

Three-scenario approach:

Bear Case: Conservative growth (e.g., 8-12%)
Base Case: Most likely scenario (e.g., 12-16%)
Bull Case: Optimistic growth (e.g., 16-20%)

Step 4: Operating Expense Modeling

Fixed/Variable Cost Analysis:

Operating expenses should model realistic operating leverage:

• Sales & Marketing: Typically 15-40% of revenue depending on business model
• Research & Development: Typically 10-30% for technology companies
• General & Administrative: Typically 8-15% of revenue, shows leverage as company scales

Key principles:

• ALL percentages based on REVENUE, not gross profit
• Model operating leverage: % should decline as revenue scales
• Maintain separate line items for S&M, R&D, G&A
• Calculate EBIT = Gross Profit - Total OpEx

Margin expansion framework:

Current State → Target State (Year 5)
Gross Margin: X% → Y% (justify based on scale, efficiency)
EBIT Margin: X% → Y% (result of revenue growth + opex leverage)

Step 5: Free Cash Flow Calculation

Build FCF in proper sequence:

EBIT
(-) Taxes (EBIT × Tax Rate)
= NOPAT (Net Operating Profit After Tax)
(+) D&A (non-cash expense, % of revenue)
(-) CapEx (% of revenue, typically 4-8%)
(-) Δ NWC (change in working capital)
= Unlevered Free Cash Flow

Working Capital Modeling:

• Calculate as % of revenue change (delta revenue)
• Typical range: -2% to +2% of revenue change
• Negative number = source of cash (working capital release)
• Positive number = use of cash (working capital build)

Maintenance vs Growth CapEx:

• Maintenance CapEx: Sustains current operations (~2-3% revenue)
• Growth CapEx: Supports expansion (additional 2-5% revenue)
• Total CapEx should align with company's growth strategy

Step 6: Cost of Capital (WACC) Research

CAPM Methodology for Cost of Equity:

Cost of Equity = Risk-Free Rate + Beta × Equity Risk Premium

Where:
- Risk-Free Rate = Current 10-Year Treasury Yield
- Beta = 5-year monthly stock beta vs market index
- Equity Risk Premium = 5.0-6.0% (market standard)

Cost of Debt Calculation:

After-Tax Cost of Debt = Pre-Tax Cost of Debt × (1 - Tax Rate)

Determine Pre-Tax Cost of Debt from:
- Credit rating (if available)
- Current yield on company bonds
- Interest expense / Total Debt from financials

Capital Structure Weights:

Market Value Equity = Current Stock Price × Shares Outstanding
Net Debt = Total Debt - Cash & Equivalents
Enterprise Value = Market Cap + Net Debt

Equity Weight = Market Cap / Enterprise Value
Debt Weight = Net Debt / Enterprise Value

WACC = (Cost of Equity × Equity Weight) + (After-Tax Cost of Debt × Debt Weight)

Special Cases:

• Net Cash Position: If Cash > Debt, Net Debt is NEGATIVE
  • Debt Weight may be negative
  • WACC calculation adjusts accordingly
• No Debt: WACC = Cost of Equity

Typical WACC Ranges:

• Large Cap, Stable: 7-9%
• Growth Companies: 9-12%
• High Growth/Risk: 12-15%

Step 7: Discount Rate Application (5-10 Year Forecast)

Mid-Year Convention:

• Cash flows assumed to occur mid-year
• Discount Period: 0.5, 1.5, 2.5, 3.5, 4.5, etc.
• Discount Factor = 1 / (1 + WACC)^Period

Present Value Calculation:

For each projection year:
PV of FCF = Unlevered FCF × Discount Factor

Example (Year 1):
FCF = $1,000
WACC = 10%
Period = 0.5
Discount Factor = 1 / (1.10)^0.5 = 0.9535
PV = $1,000 × 0.9535 = $954

Projection Period Selection:

• 5 years: Standard for most analyses
• 7-10 years: High growth companies with longer runway
• 3 years: Mature, stable businesses

Step 8: Terminal Value Calculation

Perpetuity Growth Method (Preferred):

Terminal FCF = Final Year FCF × (1 + Terminal Growth Rate)
Terminal Value = Terminal FCF / (WACC - Terminal Growth Rate)

Critical Constraint: Terminal Growth < WACC (otherwise infinite value)

Terminal Growth Rate Selection:

• Conservative: 2.0-2.5% (GDP growth rate)
• Moderate: 2.5-3.5%
• Aggressive: 3.5-5.0% (only for market leaders)

Do not exceed: Risk-free rate or long-term GDP growth

Exit Multiple Method (Alternative):

Terminal Value = Final Year EBITDA × Exit Multiple

Where Exit Multiple comes from:
- Industry comparable trading multiples
- Precedent transaction multiples
- Typical range: 8-15x EBITDA

Present Value of Terminal Value:

PV of Terminal Value = Terminal Value / (1 + WACC)^Final Period

Where Final Period accounts for timing:
5-year model with mid-year convention: Period = 4.5

Terminal Value Sanity Check:

• Should represent 50-70% of Enterprise Value
• If >75%, model may be over-reliant on terminal assumptions
• If <40%, check if terminal assumptions are too conservative

Step 9: Enterprise to Equity Value Bridge

Valuation Summary Structure:

(+) Sum of PV of Projected FCFs = $X million
(+) PV of Terminal Value = $Y million
= Enterprise Value = $Z million

(-) Net Debt [or + Net Cash if negative] = $A million
= Equity Value = $B million

÷ Diluted Shares Outstanding = C million shares
= Implied Price per Share = $XX.XX

Current Stock Price = $YY.YY
Implied Return = (Implied Price / Current Price) - 1 = XX%

Critical Adjustments:

• Net Debt = Total Debt - Cash & Equivalents
  • If positive: Subtract from EV (reduces equity value)
  • If negative (Net Cash): Add to EV (increases equity value)
• Use Diluted Shares: Includes options, RSUs, convertible securities
• Other adjustments (if applicable):
  • Minority interests
  • Pension liabilities
  • Operating lease obligations

Valuation Output Format:

Valuation Component,Amount ($M)
PV Explicit FCFs,X.X
PV Terminal Value,Y.Y
Enterprise Value,Z.Z
(-) Net Debt,A.A
Equity Value,B.B
,,
Shares Outstanding (M),C.C
Implied Price per Share,$XX.XX
Current Share Price,
how to use dcf-model
CursorClaude CodeClineCodexWindsurfGooseGitHub CopilotVS CodeGemini CLIKiloOpencodeKimi CLIRoo ClineAiderContinueZedBolt.newLovablev0Replit AgentSweepSmol DeveloperDevinCavemanAmpAntigravity
How to use dcf-model on Cursor
AI-first code editor with Composer
1
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
›Cursor installed and configured on your development machine
›Node.js version 16.0+ with npm package manager (verify with node --version)
›Active project directory or workspace where you want to add dcf-model
2
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
$npx skills add https://github.com/anthropics/financial-services-plugins --skill dcf-modelcopy
The skills CLI fetches dcf-model from GitHub repository anthropics/financial-services-plugins and configures it for Cursor.
3
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
◆ Which agents do you want to install to?
│
│ ── Universal (.agents/skills) ── always included ────
│   • Amp
│   • Antigravity
│   • Cline
│   • Codex
│ ●Cursor(selected)
│   • Cursor
│   • Windsurf
4
Verify installation
Confirm successful installation by checking the skill directory location:
.cursor/skills/dcf-model
Reload or restart Cursor to activate dcf-model. Access the skill through slash commands (e.g., /dcf-model) or your agent's skill management interface.
⚠
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
Additional Resources
›View source code on GitHub›Skills CLI documentation›Learn more about Cursor›What are agent skills?